Tongston Entreprenuership Group Recruitment 2026: Product Designer (UI/UX), Full Stack Engineer, Etc. Jobs

Tongston is a multi-award-winning brand providing entrepreneurial education, media, enterprise & finance services for sustainable socio-economic development. T-World is Tongston’s AI powered digital entrepreneurial thinking ecosystem providing integrated media, enterprise, finance and entrepreneurial education services to K-12 Students, HE Students, Entrepreneurs, Intrapreneurs and their institutions globally to become Valuable, Influential & Profitable. For more information, visit tongston.com

We are recruiting to fill the position below:

Job Title: Full Stack Engineer  (Back-End Focus — Node.js, MongoDB, AI Enablement, Web3 Exposure + Front-End Supportive – React (Web)

Location: Remote
Employment Type: Contract

Overview

• Tongston is seeking a Full Stack Engineer (Back-End Focus) to help build and scale T-World, an AI-powered platform spanning education, enterprise, media, and finance.
• This role is ideal for a backend-leaning engineer who can own APIs, data models, integrations, reliability, and AI workflows—while remaining comfortable delivering lightweight React web UI when needed to support product flows and internal tools. You will Participate in Agile ceremonies: planning, execution, review, and iteration.

Core Stack
Back-End (Primary Focus):

• Node.js with Express (API services / serverless routes where applicable)
• MongoDB (Atlas & Compass)

Front-End (Supportive):

• React (Web)
• Vite
• Tailwind CSS
• State & data: TanStack Query, Zustand

Platform & Infrastructure:

• Authentication: Firebase (synced with MongoDB)
• Storage:
  • Cloudinary (short-term media handling)
  • AWS S3 (long-term storage with immediate migration )
• CI/CD: GitHub Actions
• Security: CodeQL, Dependabot, basic OWASP-aligned practices

AI Tooling:

• LangChain (or similar orchestration frameworks)
• API-based LLM workflows

Web3 (Exposure-Level):

• Wallets, signing flows, token interactions-conversion
• On-chain vs off-chain boundaries
• (Deep smart contract development is not required)

Roles and Responsibilities
Back-End & Architecture (Primary):

• Build and maintain server-side services and APIs using Node.js and Express
• Design, implement, and optimize MongoDB schemas, indexes, and query patterns
• Own backend integrations including:
  • Authentication (Firebase)
  • Media storage (Cloudinary, AWS S3)
  • Environment configuration and secrets management
  • Logging and monitoring
• Define modular service boundaries aligned with T-World’s product structure (widgets, modules, sub-features)
• Ensure backend reliability, performance, and scalability

Front-End Support (Secondary):

• Ship or support React components required to validate backend APIs, AI flows, or admin/internal tooling
• Collaborate with frontend engineers to ensure clean API contracts and smooth UI ↔ backend interactions
• Maintain code quality via pull requests, documentation, and shared standards

AI Enablement:

• Integrate AI workflows across modules (UI → API → AI → DB)
• Support AI-powered experiences such as:
  • Assistants
  • Search
  • Content generation
• Ensure safe and reliable AI integrations, including:
  • Error handling and fallbacks
  • Latency and timeout management
  • Rate limiting and caching
  • Prompt and version management
  • Traceable outputs for debugging and evaluation

Delivery, Security & Operations:

• Support CI/CD pipelines using GitHub Actions
• Follow secure practices for:
  • Secrets and key management
  • Access control and offboarding hygiene
• Contribute to deployment, monitoring, and operational stability

Knowledge, Skills & Attitude Requirements
Technical Knowledge & Skills:

• Strong experience with Node.js and backend design patterns
• Strong experience with MongoDB (schema design, indexing, aggregation, performance tuning)
• Solid working knowledge of Express.js
• Comfort working with React for integration-level UI tasks
• Familiarity with REST APIs, server-side architecture, and environment configuration

Soft Skills & Attitude:

• Strong analytical and problem-solving skills
• Clear communication and collaboration across teams
• Ability to prioritize, execute, and deliver with attention to detail
• Ownership mindset and comfort working in a fast-paced environment
• Strong alignment with Tongston’s mission, values, and culture. Learn more about Tongston’s culture

Nice-to-Have Knowledge & Skills:

• Exposure to AI integrations (LangChain or similar)
• Familiarity with Web3 integration workflows (wallets, signing, token flows)
• Experience with background jobs, queues, or serverless patterns
• Exposure to cloud infrastructure (AWS)

Benefits

• Monthly professional fee of NGN200,000.
• A monthly Remote Productivity Support Package.
• A company-provided laptop and access to Tongston-funded platforms, software, licensed tools and other approved resources required to perform your role effectively.
• Pathway to full-time employment opportunity to secure additional benefits, including pension, HMO, statutory employee leave categories, promotion-based entitlements, and staff welfare benefits.
• Exposure to user research, product strategy, user journeys, wireframing, prototyping, usability testing, analytics-informed design improvement, and cross-functional product delivery across web, mobile and other digital platforms.
• Team-based execution and support, including an overall project management structure, reporting to a line manager, and collaboration within a sprint-based team workflow with defined weekly deliverables.
• A structured learning and growth pathway supported through twice-yearly performance review, development and growth conversations (January & July). If you join after a review cycle, your first review will take place in the next review window. The review helps you document and communicate how you’ve grown, developed and demonstrated being Valuable, Influential & Profitable.
• Learning & Development budget: NGN350,000 to support continuous upskilling, role-specific learning and broader professional development.
• Up to 10 working days of approved paid time away from active delivery annually.
• Eligible for the Tongston Annual Personnel High Performance Award which comes with cash prizes and certificates you can include in your profile for future jobs.
• Professional Visibility: listed on Tongston’s website.
• Complimentary premium access to T-World, Tongston’s integrated digital platform.
• Eligibility for discretionary performance-based bonus/allocation
• Participation in Tongston Academy sessions (scheduled periodically):
  • Personal branding (includes CV/LinkedIn review)
  • Personal finance & investing
  • Sales, communication & networking
  • Business development & strategy
  • Project management, Cybersecurity awareness & Digital automation tools.

Application Closing Date
31st August, 2026.

Method of Application
Interested and qualified candidates should:
Click here to apply online

Note

• Fill the form where you can provide information about yourself.
• Upload your CV & portfolio where applicable, and answer some basic pre-screening questions that demonstrate how you meet the knowledge, skills and attitude requirements for the role, in line with the JD
• Applications will be reviewed on a rolling basis, so we strongly encourage early submission.
• If you have any questions or clarifications, please write to us at info@tongston.com with pifhr@tongston.com in copy. Please use the subject “IC Application for – [name of the role]” in directing any correspondences to us.
• If shortlisted, you will progress through the rest of the recruitment process – technical assessment, personality & multiple intelligence check, conversation with the line manager and one or more team members, reference checks, and, if successful, an offer & if accepted, onboarding.
• Although this is a remote opportunity, candidates based in Gombe, Bauchi, Ilorin, Lagos or Abuja will be viewed favourably.
• For candidates who have not yet completed their NYSC, we may also be able to consider an NYSC engagement, particularly for those based in Gombe, Lagos or Abuja.

Job Title: AI Governance Graduate Officer

Location: Nigeria (Remote)
Employment Type: Contract

Overview

• The role is responsible for shaping, governing, testing, and coordinating the responsible deployment of AI systems powering Tongston and T-World. The purpose of the role is to ensure that AI tools, assistants, agents, knowledge-base interactions, and AI-enabled workflows are clearly defined, ethically governed, properly tested, and aligned to real product needs across Tongston’s four pillars: Enterprise, Media, Finance, and Entrepreneurial Education.
• The role owns the AI governance framework across the AI lifecycle, from use-case design and behaviour definition to prompt/KB interaction rules, knowledge-base admissibility, risk controls, output testing, governance registers, acceptance criteria, and release-readiness sign-off from a governance perspective. It ensures that AI systems are designed to improve user experience, support workflows, and uphold integrity, transparency, inclusiveness, safety, explainability, privacy, responsible data use.
• The role does not own production backend or AI engineering implementation. Instead, it defines the AI behaviour, governance rules, testing expectations, source-use boundaries, risk controls, and acceptance criteria that AI Engineering and technology teams need in order to implement reliable AI-enabled features. It also coordinates with Education, Data, AI Engineering, Back End, Front End, UI/UX, Legal/Governance, and other relevant teams to ensure that AI systems are well-specified, responsibly managed, properly tested, and suitable for live or pilot product environments.
• This role oversees AI governance testing, including hallucination review, bias review, safety review, KB admissibility review, source-use review, prompt/KB interaction review, weak-input testing, fallback testing, and escalation tracking. Where AI outputs are educational in nature, the role coordinates with Education AI Output Testers to ensure that governance-compliant outputs are also educationally accurate, curriculum-aligned, age-appropriate, pedagogically sound, and useful for users.
• The role strengthens Tongston’s Entrepreneurial Thinking Model, reward systems, knowledge-base governance, and AI-enabled product experiences by ensuring that AI design, governance, testing, and implementation-readiness are connected, documented, auditable, and continuously improved.

Roles & Responsibilities
THINK (Conceptualisation & Design):

CREATE (Development & Implementation):

SELL (Dissemination, Monetisation, Adoption & Impact):

Knowledge, Skills & Attitude Requirements
Knowledge:

• Bachelor’s Degree, HND/ND, current study, or equivalent practical experience in Computer Science, IT, Information Systems, Engineering, Data Science, Statistics, Economics, Mathematics, or another relevant technology, analytics, or quantitative field is preferred.
• Relevant training, certifications, bootcamps, or practical learning in project coordination, IT support, data analytics, QA/testing, AI tools, digital operations, or governance-related work will be an added advantage.
• Working understanding of AI systems in product environments, including LLMs, AI assistants, prompt design, prompt evaluation, basic retrieval/search, knowledge-base use, and how AI behaviour is defined, tested, and governed before implementation.
• Understanding of responsible AI concepts, including bias, fairness, explainability, transparency, safety, privacy, consent, access control, data minimisation, retention, IP/licensing, and how these translate into logs, registers, evaluation records, and audit trails.
• Understanding of knowledge-base governance for AI, including content sourcing, metadata tagging, attribution discipline, licensing labels, admissibility rules, basic retrieval concepts.
• Exposure to AI/workflow tools such as Flowise, Dify, LangChain, LangGraph, LlamaIndex, ChatGPT, Claude, Gemini, open-source LLM interfaces, or similar tools for prototyping, testing, comparison, and evaluation.
• Exposure to governance and KB tools such as metadata sheets, source registers, licensing registers, admissibility logs, bias/hallucination logs, safety/risk registers, AI issue trackers, test logs, evidence packs, and evaluation sheets.
• Basic non-implementation awareness of API-based AI workflows, KB/retrieval systems, model routing, fallback logic, agent behaviour, and high-level Backend → AI → retrieval → database → frontend response flows.

Experience:

• Up to 2 years’ relevant experience in an internship, NYSC, trainee, graduate, assistant, or junior role is preferred, particularly in AI design support, data or analytics, knowledge-base management, product or digital platform support, research, QA/testing, or technical documentation.
• Experience supporting cross-functional teams and maintaining structured documentation (e.g., testing logs, issue trackers, audit trails, summaries, or compliance-related records) is an added advantage.

Technical Skills:

• Ability to support AI prompt design, structured testing, output review, failure-pattern identification, and evaluation criteria development.
• Ability to use approved AI/workflow tools such as Flowise, Dify, LangChain, ChatGPT-style tools, or similar platforms for prototyping, testing, documentation, and governance support.
• Ability to support knowledge-base governance, including metadata tagging, content organisation, source tracking, licensing labels, attribution records, and Green/Yellow/Red classification.
• Ability to maintain AI governance artefacts, including test logs, issue registers, bias/hallucination records, incident notes, content inventories, consent/attribution records, and performance summaries.
• Ability to review AI performance at a basic level by identifying strong vs weak outputs, recurring edge cases, user-confusion risks, and issues requiring escalation or refinement.
• Comfortable using spreadsheets, trackers, registers, and documentation tools to organise AI testing results, governance records, workflow notes, and stakeholder-ready summaries.

Attitude:

• Strong ethics and integrity; careful handling of sensitive data and model outputs.
• Detail-oriented, structured, and quality-focused (traceability, accuracy, repeatability).
• Proactive improvement mindset: flags risks early, proposes fixes, and learns quickly.
• Strong analytical, problem-solving, organizational and communication skills.
• Ability to prioritize, and execute projects / tasks to a deadline with attention to detail.
• You must align with and be determined to have a fit with Tongston’s culture.

Benefits

• Monthly professional fee of NGN140,000.
• A monthly Remote Productivity Support Package.
• A company-provided laptop and access to Tongston-funded platforms, software, licensed tools and other approved resources required to perform your role effectively.
• Pathway to full-time employment opportunity to secure additional benefits, including pension, HMO, statutory employee leave categories, promotion-based entitlements, and staff welfare benefits. See our career page for more info.
• Exposure to user research, product strategy, user journeys, wireframing, prototyping, usability testing, analytics-informed design improvement, and cross-functional product delivery across web, mobile and other digital platforms.
• Team-based execution and support, including an overall project management structure, reporting to a line manager, and collaboration within a sprint-based team workflow with defined weekly deliverables.
• A structured learning and growth pathway supported through twice-yearly performance review, development and growth conversations (January & July). If you join after a review cycle, your first review will take place in the next review window. The review helps you document and communicate how you’ve grown, developed and demonstrated being Valuable, Influential & Profitable.
• Learning & Development budget: NGN150,000 to support continuous upskilling, role-specific learning and broader professional development.
• Up to 10 working days of approved paid time away from active delivery annually.
• Eligible for the Tongston Annual Personnel High Performance Award which comes with cash prizes and certificates you can include in your profile for future jobs.
• Professional Visibility: listed on Tongston’s website.
• Complimentary premium access to T-World, Tongston’s integrated digital platform. Learn more at t-world.tongston.com
• Eligibility for discretionary performance-based bonus/allocation
• Participation in Tongston Academy sessions (scheduled periodically):
  • Personal branding (includes CV/LinkedIn review)
  • Personal finance & investing
  • Sales, communication & networking
  • Business development & strategy
  • Project management, Cybersecurity awareness & Digital automation tools.

Application Closing Date
31st August, 2026.

Method of Application
Interested and qualified candidates should:
Click here to apply online

Note

• This role is not expected to build production backend systems, production AI agents, or production engineering workflows. The role should understand the implementation environment well enough to define clear requirements, test AI behaviour, document risks, support validation prototypes, and provide governance inputs that engineering teams can implement reliably.How to Indicate Interest for the Role
• Please complete the application form provided here where you can provide information about yourself, upload your CV & portfolio where applicable, and answer some basic pre-screening questions that demonstrate how you meet the knowledge, skills and attitude requirements for the role, in line with the JD, no later than 31 August 2026.
• Applications will be reviewed on a rolling basis, so we strongly encourage early submission.
• If you have any questions or clarifications, please write to us at info@tongston.com with pifhr@tongston.com in copy. Please use the subject “IC Application for – [name of the role]” in directing any correspondences to us.
• If shortlisted, you will progress through the rest of the recruitment process – technical assessment, personality & multiple intelligence check, conversation with the line manager and one or more team members, reference checks, and, if successful, an offer & if accepted, onboarding.
• Although this is a remote opportunity, candidates based in Gombe, Bauchi, Ilorin, Lagos or Abuja will be viewed favourably. For candidates who have not yet completed their NYSC, we may also be able to consider an NYSC engagement, particularly for those based in Gombe, Lagos or Abuja.

Job Title: Knowledge Base (KB) Reviewer & AI Output Tester 

Location: Remote
Employment Type: Contract

Overview

• Tongston is looking for a KB Reviewer & AI Output Tester to support the Education workstream for T-World and the wider Tongston ecosystem.
• The role combines independent knowledge-base review, moderation checks and AI output testing across user-uploaded knowledge base (KB), internally generated KB materials, and developed KB objects prepared for AI or product use.
• This role sits under the Education workstream because KB Review and AI Output Testing are part of T-World’s curriculum, teaching, assessment and VIP development foundation.
• The role works closely with the Education Lead, Internal KB Designer, KB Licensor & Developer, AI Governance, AI Engineering, Technology, Data, Media/Information, Administration & PM and Legal, Policy, Regulation, Governance & Compliance (LPRGC) where required.
• This role is for someone who can operate with ownership, careful judgement, strong documentation discipline and weekly delivery accountability in a fast-moving AI-enabled product environment.

Role Purpose

• The purpose of this role is to own the independent KB review and AI-output validation layer: reviewing whether KB materials are safe, appropriate, accurate, traceable and ready for use, and testing whether AI outputs remain grounded in the approved KB and aligned with expected user intent.

The role helps Tongston answer:

• Are user-uploaded KB items, attachments, URLs, text objects and other content suitable to enter or remain in the KB workflow?
• Are internally generated KB materials from the Internal KB Designer complete, consistent, appropriately moderated and ready for downstream use?
• Are externally developed KB objects from the KB Licensor & Developer properly documented, traceable and fit for review/testing?
• Does the AI retrieve from approved KB objects instead of guessing, hallucinating or producing unsupported claims?
• Where are moderation failures, retrieval failures, prompt/input misalignment, KB gaps, bias risks, unsuitable content or recurring output-quality issues appearing?
• What needs to be returned for revision, escalated to AI Governance / LPRGC, handed to AI Engineering / Technology, or fed back within Education?

Roles & Responsibilities
THINK (Review Logic, Moderation Planning & AI Test Design):

• Translate Education Lead / KB Lead priorities into clear review batches, moderation-check plans, AI test scenarios, expected-output notes and weekly deliverables.
• Define review scope for assigned user-uploaded KB content, internally generated KB materials, external KB objects, text objects, URL objects, attachment objects, prompt libraries, AI instructions, course/assessment materials and related workflow items.
• Apply approved KB review, acceptable-use, platform-integrity, legitimacy/authenticity, plagiarism/copyright-plausibility, curriculum-alignment, user-context and escalation criteria consistently.
• Plan AI output tests using approved prompts, dropdown-led inputs, free-text inputs, user journeys, feature flows, KB objects and expected outputs.
• Identify likely edge cases, including incomplete inputs, ambiguous queries, conflicting user intent, unsuitable uploads, missing KB context, weak metadata, wrong tags, outdated content and high-risk AI responses.
• Distinguish between content-quality issues, moderation issues, KB structure issues, source/permissions issues, AI-governance issues, prompt/input issues, retrieval issues, product-flow issues and technology implementation issues.
• Flag sensitive, unclear, borderline, restricted, biased, unsafe, misleading, unsupported, legally sensitive or policy-sensitive cases early instead of making unsupported assumptions.

CREATE (Review KB Materials, Run AI Tests & Maintain Logs):

• Review all assigned user-uploaded KB content and user-generated KB objects, including URLs, text, attachments, documents, links, media-related objects, profile/story-dashboard objects, learning submissions and other uploaded materials where assigned.
• Review internally generated KB materials created by the Internal KB Designer, including curriculum, teaching, assessment, VIP logic, defined terms, AI prompts, AI instructions, course pathways, rubrics and internal KB objects.
• Review developed KB objects from the KB Licensor & Developer for traceability, metadata completeness, source/status clarity, naming, tags, object relationships, handoff notes and readiness for AI/product use.
• Conduct moderation checks for acceptable use, platform integrity, legitimacy/authenticity, suspicious or misleading claims, inappropriate content, spam/manipulation indicators, unsupported assertions, bias/fairness concerns and escalation triggers.
• Check content for accuracy, relevance, clarity, completeness, curriculum alignment, pedagogical usefulness, user-context appropriateness, assessment/VIP logic alignment, defined-term consistency and AI-readiness.
• Record review decisions clearly as approved, approved with conditions, return for revision, escalate, block, restrict, monitor, deprecate, retest or not ready, using the approved tracker or workbook.
• Run structured AI output tests across approved prompts, input fields, dropdown selections, free-text queries, KB retrieval scenarios and assigned T-World feature flows.
• Assess AI outputs for accuracy, relevance, completeness, clarity, consistency, user-intent alignment, KB grounding, moderation compliance and appropriateness for the intended user journey.
• Identify and document hallucinations, unsupported claims, retrieval failures, KB gaps, prompt/input misalignment, wrong recommendations, inconsistent answers, overclaiming, weak fallback behaviour and repeated output-quality issues.
• Support retesting after updates to KB entries, prompts, metadata, tags, field structures, AI logic, moderation rules or product flows.
• Maintain clean KB Review Logs, AI Test Logs, issue logs, escalation records, retest notes, pattern summaries and handoff notes.

SELL (Handoff, Escalation, Pattern Feedback & Improvement):

• Produce clear weekly or deliverable-based updates showing items reviewed, AI tests completed, approvals, blocks, revisions, escalations, recurring issues, risks and next actions.
• Provide clear feedback to the Internal KB Designer, KB Licensor & Developer, Education Lead, AI Governance, AI Engineering, Technology, Data and other relevant teams.
• Escalate unclear, borderline, recurring, sensitive or high-risk moderation issues to the correct owner rather than normalising weak or unsafe behaviour.
• Report recurring AI output problems to AI Governance and AI Engineering, including hallucination patterns, rejected-content patterns, biased outcomes, incorrect recommendations, weak retrieval, poor user-intent alignment or moderation false positives/negatives.
• Recommend practical improvements to KB templates, metadata rules, tagging, prompts, input fields, expected-output rules, review checklists, moderation categories and AI test scenarios.
• Support periodic review, clean-up, replacement, deprecation or re-testing of KB objects where content becomes outdated, superseded, unapproved, unsafe, poorly performing or no longer fit for purpose.
• Supervise or coordinate KB Reviewer Volunteers and KB AI Output Tester Volunteers where assigned, including task allocation, output checks, feedback notes and escalation discipline.
• Keep all files, review logs, test records, evidence, screenshots, issue notes, handoff notes and outputs well named, versioned, permissioned and easy to retrieve for future team use.
• Fulfil additional tasks as required that are incidental to the above.

Expected Outputs:

• KB Review Logs covering user-uploaded, internally generated and developed KB items.
• Moderation check records, including acceptable-use, platform-integrity and legitimacy/authenticity notes.
• Review decisions, revision notes, escalation notes and approval/rejection status updates.
• AI Test Logs with input used, expected output, actual AI response, issue observed, severity, suspected cause, owner and next action.
• Hallucination, retrieval-failure, prompt/input misalignment, KB gap and moderation-failure logs.
• Retest validation notes after KB, prompt, metadata, field-structure, AI logic or moderation updates.
• Pattern summaries and weekly delivery updates.
• Handoff notes to Internal KB Design, KB Licensor & Developer, AI Governance, AI Engineering, Technology, Data, LPRGC or other relevant teams.
• Recommendations for improving KB quality, moderation rules, prompt logic, tagging, metadata, user inputs and AI-output behaviour.

Knowledge, Skills & Attitude Requirements
Experience Level:

• Ideal for an early-career candidate (12-24 months) of either relevant internship, volunteering, consulting, project, or professional work experience in either content moderation, research review, quality assurance, assessment, AI output testing, education content review or product operations.

Knowledge:

• Bachelor’s degree, Diploma, HND/ND, postgraduate certificate or equivalent in either of the following disciplines is Education, Law, Social Sciences, Research, Data, Information Management, Knowledge Management, Computer Science, Product, Communications, Technology Policy or related fields is preferred, but not required.
• Working awareness of either content moderation, acceptable use, platform integrity, legitimacy/authenticity, misinformation/misleading-content indicators, plagiarism/copyright-plausibility, bias/fairness, user safety, confidentiality and escalation logic is useful.
• Understanding of how KB quality affects AI-enabled search, user guidance, user-uploaded content workflows, moderation and recommendations for curriculum, assessment, or other forms of content.
• Awareness of AI output risks such as hallucination, unsupported claims, wrong retrieval, prompt/input misalignment, weak fallback behaviour, overclaiming, inappropriate recommendations and inconsistent answers is useful but not required.
• Awareness of assessment integrity, fairness, confidentiality, anti-cheating principles, and unbiased marking is useful but not required.
• Understanding of Tongston’s education, enterprise, media, finance pillars; T-World and entrepreneurial thinking model is an advantage. We encourage you to take some time to go through our website and third party platforms for more information.

Technical Skills:
Required:

• Strong reading comprehension, review, writing, editing and issue-documentation skills
• Ability to follow and apply structured review frameworks, moderation rules, AI test scripts, checklists, registers, trackers or escalation workflows as provided.
• Ability to use Google Workspace / Microsoft Office tools effectively.
• Strong spreadsheet and tracker-management skills in Excel or Google Sheets, such as clean data entry, filters, status tracking, documenting issue logs, and issuing handoff notes.

Useful but not required:

• Ability to compare expected versus actual AI outputs and identify hallucinations, unsupported claims, missing KB context, weak retrieval, inconsistent behaviour or poor user-intent alignment.
• Ability to review KB objects for metadata completeness, tags, naming, source/status clarity, version control etc.
• Ability to use approved AI tools responsibly for review support, comparison, test design, issue categorisation, drafting and quality-checking while preserving human judgement, confidentiality and traceability.

Soft Skills & Attitude:

• Strong analytical, problem-solving and issue-spotting skills.
• High attention to detail and strong ownership mindset.
• Clear written communication and concise escalation notes.
• Ability to prioritise, execute and deliver with speed, accuracy and attention to detail in a remote environment.
• Comfortable challenging weak content, unsafe uploads, unclear moderation outcomes, poor outputs, incomplete metadata and unsupported assumptions respectfully.
• Curious, proactive, discreet and committed to continuous learning.
• Comfortable working in a fast-paced, cross-functional team with weekly deliverables.
• Strong alignment with Tongston’s mission, values and culture.

Benefits

• Monthly professional fee of NGN125,000.
• A monthly Remote Productivity Support Package.
• A company-provided laptop and access to Tongston-funded platforms, software, licensed tools and other approved resources required to perform the role effectively, subject to approval and availability.
• Pathway to full-time employment opportunity to secure additional benefits, including pension, HMO, statutory employee leave categories, promotion-based entitlements and staff welfare benefits, subject to performance, fit, role availability and organisational needs.
• Exposure to KB review, moderation checks, user-uploaded content review, internal KB validation, AI-output testing, hallucination/retrieval-failure detection, prompt/input alignment, metadata discipline, AI-enabled product workflows and cross-functional product delivery across Tongston’s pillars.
• Team-based execution and support, including an overall project management structure, reporting to a line manager, and collaboration within a sprint-based team workflow with defined weekly deliverables.
• A structured learning and growth pathway supported through twice-yearly performance review, development and growth conversations (January & July).
• If you join after a review cycle, your first review will take place in the next review window.
• The review helps you document and communicate how you have grown, developed and demonstrated being Valuable, Influential & Profitable.
• Learning & Development budget: NGN100,000 to support continuous upskilling, role-specific learning and broader professional development.
• Up to 10 working days of approved paid time away from active delivery annually.
• Eligible for Tongston Annual Personnel High Performance Award which comes with cash prizes and certificates you can include in your profile for future jobs.
• Professional Visibility: listed on Tongston’s website.
• Complimentary premium access to T-World, Tongston’s integrated digital platform. Learn more at https://t-world.tongston.com/
• Eligibility for discretionary performance-based bonus/allocation.
• Participation in Tongston Academy sessions, scheduled periodically, which may include personal branding, personal finance and investing, sales, communication and networking, business development and strategy, project management, cybersecurity awareness and digital automation tools.

Application Closing Date
31st August, 2026.

Method of Application
Interested and qualified candidates should:
Click here to apply online

How to Indicate Interest for the Role

• Please complete the application form provided where you can provide information about yourself, upload your CV & portfolio where applicable, and answer some basic pre-screening questions that demonstrate how you meet the knowledge, skills and attitude requirements for the role, in line with the JD, no later than 31 August 2026. Applications will be reviewed on a rolling basis, so we strongly encourage early submission.
• If you have any questions or clarifications, please write to us at info@tongston.com with pifhr@tongston.com in copy. Please use the subject “IC Application for – [name of the role]” in directing any correspondences to us.
• If shortlisted, you will progress through the rest of the recruitment process – technical assessment, personality & multiple intelligence check, conversation with the line manager and one or more team members, reference checks, and, if successful, an offer & if accepted, onboarding.
• Although this is a remote opportunity, candidates based in Gombe, Bauchi, Ilorin, Lagos or Abuja will be viewed favourably. For candidates who have not yet completed their NYSC, we may also be able to consider an NYSC engagement, particularly for those based in Gombe, Lagos or Abuja.

Job Title: Product Designer (UI/UX)

Location: Remote
Employment Type: Contract

Overview

• Support the design, improvement, coordination and quality assurance of Tongston’s digital products, platforms and user experiences, including T-World, Tongston websites, client-facing websites managed by the company, and selected third-party software/tools configured for company or client use.
• The role combines UI/UX design, user research, product improvement, testing, documentation, stakeholder coordination and implementation follow-through, with the expectation that the role holder develops into a broader product management capacity over time.
• This is a 100% remote role full-time This is a full-time paid independent contractor engagement for 12 months.

Roles and Responsibilities

• Collaborate with cross-functional teams including Data, Research & Economics, Education, Strategy, Media/Info, Operations and Technology to translate user, business and operational needs into effective digital product and experience improvements.
• Conduct and support user research, usability testing and feedback analysis using surveys, interviews, analytics and other tools to inform product, design and feature decisions.
• Design and refine user journeys, user flows, wireframes, prototypes, site maps, mock-ups and related product/design documentation for web, mobile and other digital platforms.
• Support the design, review and improvement of Tongston’s digital ecosystem, including T-World, company websites, internal tools, client-managed websites and selected third-party platforms configured for business or client use.
• Monitor and analyze feedback, usage data, performance metrics and quality indicators to identify gaps, friction points and opportunities for continuous improvement.
• Conduct routine testing, QA and user acceptance reviews across websites, apps and configured software platforms to ensure usability, accessibility, responsiveness, consistency and overall quality.
• Maintain consistency across products through design standards, reusable patterns, style guides and structured documentation of product and design decisions.
• Contribute to product strategy, roadmap refinement, benchmarking and release planning through research-backed recommendations and practical implementation insight.
• Support user adoption and product continuity through guides, walkthroughs, handover notes and other supporting materials as required.

Knowledge, Skills & Attitude Requirements
Technical Experience:

• Relevant qualification in Product Management, Computer Science, Business Administration, or a related field.
• 1 – 2 years of relevant experience in UI/UX, product design or digital product support (wireframes, website mapping, storyboards, user process flows, etc.) across web and mobile platforms (especially mobile).
• Exposure to no-code/low-code tools, CMS platforms or third-party software configuration.
• Experience with participating in the deployment of web and mobile applications; and interacting with users/tracking user feedback is useful.
• Experience working across cross-functional teams and collaborating with developers, designers, data analysts & Scientists, media, education and other such personnel; and supporting testing, feedback collection or post-launch improvements is useful.

Technical Knowledge:

• Good knowledge of UI/UX best practices and user-centered design principles.
• Good understanding of SEO principles and ensuring that UI/UX designs will adhere to them.
• Good understanding of usability, accessibility, consistency and quality assurance across digital products and platforms and product thinking, including user needs, problem definition, feature refinement and continuous improvement.
• Basic knowledge of image authoring tools, to be able to crop, resize, refine, or perform adjustments on an image.
• Familiarity with data management, analytics, and performance tracking tools is useful.
• Understanding of app development processes, API and third-party integrations; and developer handoff requirements is useful.

Technical Skills:

• Excellent visual design skills & principles and proficiency in Figma.
• Strong writing or copy structuring ability for digital interfaces, prompts, labels, guidance text and user-facing content.
• Proficiency in using Git version control.
• Ability to work closely with developers and relevant technical teams to ensure timely implementation of agreed requirements, issue resolution and alignment between business needs, user experience and technical delivery.
• Ability to apply product thinking to help define user needs, problem statements, use cases, feature requirements, priorities and phased improvement opportunities.
• Proficiency in HTML, CSS (SCSS) and Adobe Creative Suite is useful.
• Familiarity with tools such as Gimp or Photoshop is useful.

Soft Skills & Attitude:

• Strong problem-solving and analytical skills
• Good communication and collaboration abilities
• Ability to manage tasks and meet deadlines in a remote environment
• High attention to detail and design quality.
• Curious, proactive, and committed to continuous learning
• Comfortable working in a fast-paced, cross-functional team
• Strong alignment with Tongston’s mission, values, and culture.

Benefits

• Monthly professional fee of NGN120,000.
• A monthly Remote Productivity Support Package.
• A company-provided laptop and access to Tongston-funded platforms, software, licensed tools and other approved resources required to perform your role effectively.
• Pathway to full-time employment opportunity to secure additional benefits, including pension, HMO, statutory employee leave categories, promotion-based entitlements, and staff welfare benefits.
• Exposure to user research, product strategy, user journeys, wireframing, prototyping, usability testing, analytics-informed design improvement, and cross-functional product delivery across web, mobile and other digital platforms.
• Team-based execution and support, including an overall project management structure, reporting to a line manager, and collaboration within a sprint-based team workflow with defined weekly deliverables.
• A structured learning and growth pathway supported through twice-yearly performance review, development and growth conversations (January & July). If you join after a review cycle, your first review will take place in the next review window. The review helps you document and communicate how you’ve grown, developed and demonstrated being Valuable, Influential & Profitable.
• Learning & Development budget: NGN200,000 to support continuous upskilling, role-specific learning and broader professional development.
• Up to 10 working days of approved paid time away from active delivery annually.
• Eligible for the Tongston Annual Personnel High Performance Award which comes with cash prizes and certificates you can include in your profile for future jobs.
• Professional Visibility: listed on Tongston’s website.
• Complimentary premium access to T-World, Tongston’s integrated digital platform.
• Eligibility for discretionary performance-based bonus/allocation.

Participation in Tongston Academy sessions (scheduled periodically):

• Personal branding (includes CV/LinkedIn review).
• Personal finance & investing.
• Sales, communication & networking.
• Business development & strategy.
• Project management, Cybersecurity awareness & Digital automation tools.

Application Closing Date
31st August, 2026.

Method of Application
Interested and qualified candidates should:
Click here to apply online

Note

• Fill the form where you can provide information about yourself.
• Upload your CV & portfolio where applicable, and answer some basic pre-screening questions that demonstrate how you meet the knowledge, skills and attitude requirements for the role, in line with the JD, no later than 31 August 2026.
• Applications will be reviewed on a rolling basis, so we strongly encourage early submission.
• If you have any questions or clarifications, please write to us at info@tongston.com with pifhr@tongston.com in copy. Please use the subject “IC Application for – [name of the role]” in directing any correspondences to us.
• If shortlisted, you will progress through the rest of the recruitment process – technical assessment, personality & multiple intelligence check, conversation with the line manager and one or more team members, reference checks, and, if successful, an offer & if accepted, onboarding.
• Although this is a remote opportunity, candidates based in Gombe, Bauchi, Ilorin, Lagos or Abuja will be viewed favourably.
• For candidates who have not yet completed their NYSC, we may also be able to consider an NYSC engagement, particularly for those based in Gombe, Lagos or Abuja.

Job Title: AI & Agent Development Engineer
Location: Remote
Employment Type: Contract

Overview

• Tongston is seeking an AI & Agent Development Engineer to translate Tongston’s AI strategy, governance requirements, product specifications, KB logic, user-context logic, and model-routing decisions into production-ready AI workflows within a platform.
• This role is ideal for an early-career AI engineering professional who can help build, integrate, test, and improve AI-powered product features across the stack, including agent workflows, LLM-enabled experiences, retrieval logic, APIs, and supporting backend systems.
• This role is not limited to embedding third-party AI APIs. It requires practical understanding of LLM orchestration, open-source model selection, multi-model workflow design, retrieval systems, compute infrastructure, AWS-based deployment considerations, cost optimisation, and secure integration into T-World’s existing GitHub codebase and platform architecture. It will operationalize the AI layer by combining approved open-source LLMs, selected closed-model APIs where justified, internal knowledge-base logic, user data, platform permissions, and governed workflow orchestration into reliable AI-enabled product features.
• You will work closely with education, AI, data/research/economics team members; and a cross functional IT team of UX/UI designers, backend & front-end engineers, and other key team members/stakeholders. You will participate in Agile ceremonies including planning, development, testing, and iteration.

Core Stack:
Engineering & LLM Orchestration:

• Flowise, Dify, LangChain, LangGraph, LlamaIndex, or similar orchestration frameworks
• API-based LLM workflows
• Open-source LLM integration and evaluation
• Multi-model / multi-layer LLM orchestration
• Dynamic function invocation using OpenAI / GPT-wrapper or equivalent where approved

Back-End:

• Node.js with Express (API services / serverless routes where applicable)
• MongoDB (Atlas & Compass)
• API services and serverless routes where applicable
• Authentication: Firebase (synced with MongoDB)
• Storage: AWS S3 including S3, Lambda, Step Functions, State Machines, Bedrock where applicable, and related cloud services
• CI/CD: GitHub Actions

Front-End:

• Reactjs, Typescript, Tanstack-Router/Querry, Zustand

Roles and Responsibilities

• Build, implement, improve, and operationalize AI agents, assistant workflows, retrieval flows, and LLM-powered product features for T-World using approved tools, frameworks, orchestration platforms, APIs, open-source models, and code-based approaches as appropriate.
• Translate product, user, AI governance, KB, and platform requirements into working technical flows, including user input handling, prompt orchestration, model routing, retrieval logic, guardrails, state handling, tool/function calling, fallback behaviour, and output delivery.
• Support the development of T-World’s proprietary multi-layer AI model by combining approved open-source LLMs, embeddings, retrieval systems, internal KB structures, user-context logic, and task-specific model routing into governed and reusable AI workflows.
• Evaluate and recommend suitable LLMs or AI components for specific tasks, considering model capability, cost, latency, licensing, privacy, reliability, deployment feasibility, and whether the model should be used for free/basic functionality or premium/pay-per-use functionality.
• Implement workflows that reduce unnecessary dependency on major closed-model providers, while still allowing approved premium model usage where advanced reasoning, accuracy, or performance justifies the cost.
• Work with compute and cloud infrastructure considerations, particularly AWS, to ensure AI workflows can run, scale, store data, retrieve data, log activity, and handle latency or failure in a production-oriented environment.
• Implement backend services, APIs, retrieval layers, storage logic, and integration logic required to power AI features across web and mobile product experiences, while aligning closely with the wider engineering architecture.
• Incorporate AI-related code into the existing T-World GitHub codebase in a clean, reviewable, maintainable, and modular manner, using appropriate branches, pull requests, documentation, and handover notes.
• Work closely with backend, frontend, and full-stack engineers to ensure clean AI integration across UI → API → AI orchestration → retrieval → database → output.
• Implement application logic and structured data flows in MongoDB and related systems to support AI-enabled use cases, including retrieval, personalization, content mapping, user-specific recommendations, traceable workflow behaviour, and analytics-linked AI outputs.
• Build, test, and optimize agent workflows using platforms such as Flowise, Dify, LangChain, LangGraph, LlamaIndex, or other approved orchestration tools, while supporting movement beyond no-code or low-code setups where greater control, customization, maintainability, or scale is required.
• Implement retrieval and knowledge-base integration patterns, including storage and access logic for structured and semi-structured content, references, metadata, tagging logic, permissions, and linked evidence.
• Implement technical logic that allows T-World AI to suggest, prefill, personalize, validate, or generate outputs across the platform, ensuring that outputs respect backend permissions, visibility rules, approved data-source rules, moderation states, and restricted-content controls.
• Support AI-linked platform behaviour such as premium AI workflows, free-tier AI workflows, model fallback, usage limits, cost tracking, and escalation to higher-cost models only where justified.
• Collaborate with other engineers on AI-enabled experiences in the app, including AI-powered assistants, search, recommendations, autofill, content generation, workflow suggestions, and widget-to-widget AI journeys.
• Support latency management, loading states, fallback messages, retries, error handling, degraded-mode behaviour, and resilience patterns for AI-enabled features.
• Handle weak input, no results, AI failure, timeouts, partial retrieval, partial model failure, and insufficient-context scenarios with clear fallback behaviour.
• Log AI requests, model calls, retrieval events, outputs, failures, fallback events, premium-model usage, and relevant debugging information for review, monitoring, cost control, and future improvement.
• Enforce backend permissions, visibility rules, moderation states, and KB approval status across all AI outputs.
• Write clean, maintainable, secure, and well-documented code, ensuring clear separation across API, AI orchestration, model routing, retrieval, data, logging, and platform-integration layers.
• Design and execute testing for AI systems, including weak or empty input, no-result scenarios, AI failure or timeout, model fallback, cost-trigger thresholds, consistency, permission enforcement, and workflow reliability.
• Work with substantive reviewers, QA colleagues, AI Governance, Education, Data, Back End, Front End, and UI/UX teams to ensure that outputs are technically functional, contextually appropriate, governed, usable, operationally fit for purpose.
• Support deployment, release readiness, monitoring, and iterative improvement of AI-enabled features in live or staging environments, including coordination on versioning, configuration, testing, observability, and stable release cycles.
• Maintain technical documentation covering model choices, orchestration workflows, API dependencies, AWS/compute assumptions, retrieval logic, testing outcomes, implementation decisions, risks, and handover notes.
• Escalate major technical, product, model, integration, compute, reliability, cost, privacy, or architectural risks to management in a timely manner.
• Ensure all AI-enabled features are production-ready, reliable, cost-conscious, secure, maintainable, and aligned with Tongston’s long-term goal of building T-World’s AI layer.
• Carry out additional tasks as required by management in support of product goals & req’s.

Production-Readiness Expectations
All AI-enabled features built under this role must be suitable for real product environments, not just prototypes. This includes:

• Clear handling of:
  • AI failure or timeout
  • Weak or insufficient input
  • No-result retrieval scenarios
  • Partial system failure (e.g., retrieval works but AI fails)
• Ensuring:
  • Only approved and permitted data is used in outputs
  • Rejected or restricted content never appears in outputs
  • AI does not bypass backend validation or permissions
• Implementing:
  • Fallback behaviour where AI confidence is low
  • Retry or degradation strategies where applicable
  • Dtructured logging for AI requests, failures, and outputs
• Designing for:
  • Maintainability and handover
  • Traceability and debugging
  • Real-world latency and user experience constraints

In addition, the role must ensure that AI-enabled features are designed for:

• Model-routing control open-source and closed-model separation cost optimisation and premium-use logic compute and cloud infrastructure constraints AWS deployment readiness where applicable secure retrieval and storage GitHub-based maintainability traceability of model calls and outputs clear fallback when cheaper/free models are insufficient future extensibility toward a more proprietary T-World AI layer
• The role is expected to think beyond “the AI works” and ensure that the AI system is reliable, safe, scalable, cost-conscious, maintainable, and strategically owned by Tongston as much as possible.

Knowledge, Skills & Attitude Requirements
Experience Level:

• This role is most ideal for early-career engineers who has hands-on experience building backend systems and has also begun working practically with LLMs, AI agents, retrieval workflows, or AI-enabled product features.
• Relevant experience may include personal projects, internships, volunteering, open-source work, hackathons, freelance engagements, research projects, or professional roles involving AI workflows, backend engineering, agent integration, API integration, cloud infrastructure, or product implementation.
• The ideal candidate does not need to have trained a foundation model from scratch, but must understand how modern AI systems are practically assembled using APIs, open-source models, orchestration frameworks, retrieval systems, user-context logic, cloud infrastructure, and product code.

Technical Knowledge & Skills

• Degree, HND/ND, current study, or equivalent practical experience in Computer Science, Software Engineering, Data/Analytics, Information Systems, Mathematics, Statistics, Engineering, AI/ML, or related fields.
• Working knowledge of Node.js, Express, REST APIs, third-party API integration, internal service integration, and server-side logic required to connect user actions, platform data, AI workflows, storage, authentication, and output delivery.
• Working knowledge of MongoDB, MongoDB Atlas, and MongoDB Compass, including schemas, collections, query logic, data validation, debugging, and structuring/retrieving data for AI-enabled use cases.
• Experience or strong practical exposure to LLM APIs, agent workflows, prompt orchestration, retrieval logic, tool/function calling, model routing, fallback logic, and structured AI integrations for product features such as suggestions, autofill, personalisation, recommendations, search, and content generation.
• Working awareness of open-source/lightweight LLMs, small language models, domain-specific models, embedding models, rerankers, and model repositories such as Hugging Face; with ability to assess models based on task fit, accuracy, latency, cost, licensing, privacy, deployment feasibility, and integration constraints.
• Ability to support Tongston’s goal of building a proprietary T-World AI layer by combining approved models, retrieval systems, internal KB logic, user-context logic, permissions, and governed orchestration flows, rather than relying only on major closed LLM providers.
• Familiarity with AWS and AI-related infrastructure, including S3, Lambda, Step Functions, State Machines, Bedrock where applicable, storage, logging, scaling, latency, cost, and the compute infrastructure needed to run, call, host, or orchestrate AI/LLM workflows.
• Familiarity with authentication, Firebase Authentication, secure access patterns, backend visibility rules, moderation states, approved data-source rules, and how to ensure AI outputs do not bypass platform permissions or backend validation.
• Ability to contribute AI-related code into the existing T-World GitHub codebase using branches, pull requests, review cycles, documentation, issue tracking, and release workflows, while avoiding disconnected prototypes.
• Ability to test and troubleshoot AI workflows across UI → API → AI orchestration → retrieval → database → output flows, including weak input, no-result retrieval, timeout, failure, fallback behaviour, logging, monitoring, traceability, maintainable code, and handover documentation

Soft Skills & Attitude:

• Strong analytical and problem-solving skills
• Clear written and verbal communication
• Ability to prioritize and execute tasks independently in a remote environment to schedule
• High attention to detail and ownership mindset
• Curious, proactive, and committed to continuous learning
• Strong alignment with Tongston’s mission, values, and culture. Learn more about Tongston’s culture: https://tongston.com/about

Nice-to-Have Knowledge & Skills

• Experience building internal tools, admin panels, or workflow automation that support KB maintenance, QA, review, analytics, reporting, or operational oversight.
• Ability to collaborate with front-end engineers on AI-linked UI behaviour, including prompts, suggestion panels, autofill options, loading states, fallback messages, error states, review/edit flows, and generated-output displays.
• Experience with LangChain, LangGraph, LlamaIndex, Flowise, Dify, or similar orchestration frameworks.
• Experience with vector databases, embeddings, semantic search workflows, reranking, chunking, metadata filtering, and retrieval evaluation.
• Experience with AI-powered search, assistants, recommendations, content generation, autofill, summarisation, classification, or related AI-enabled product features.
• Exposure to CI/CD, GitHub Actions, deployment pipelines, staging environments, and production support practices.
• Experience with model evaluation, prompt testing, AI workflow testing, red-teaming, fallback testing, or quality assurance for AI outputs.
• Basic Web3 exposure where relevant to wallets, signing flows, token interactions/conversion, and on-chain vs off-chain boundaries.

Salary and Benefits

• Monthly professional fee of NGN175,000.
• A monthly Remote Productivity Support Package.
• A company-provided laptop and access to Tongston-funded platforms, software, licensed tools and other approved resources required to perform your role effectively.
• Pathway to full-time employment opportunity to secure additional benefits, including pension, HMO, statutory employee leave categories, promotion-based entitlements, and staff welfare benefits. See our career page for more info.
• Exposure to user research, product strategy, user journeys, wireframing, prototyping, usability testing, analytics-informed design improvement, and cross-functional product delivery across web, mobile and other digital platforms.
• Team-based execution and support, including an overall project management structure, reporting to a line manager, and collaboration within a sprint-based team workflow with defined weekly deliverables.
• A structured learning and growth pathway supported through twice-yearly performance review, development and growth conversations (January & July). If you join after a review cycle, your first review will take place in the next review window. The review helps you document and communicate how you’ve grown, developed and demonstrated being Valuable, Influential & Profitable.
• Learning & Development budget: NGN200,000 to support continuous upskilling, role-specific learning and broader professional development.
• Up to 10 working days of approved paid time away from active delivery annually.
• Eligible for the Tongston Annual Personnel High Performance Award which comes with cash prizes and certificates you can include in your profile for future jobs.
• Professional Visibility: listed on Tongston’s website.
• Complimentary premium access to T-World, Tongston’s integrated digital platform.
• Eligibility for discretionary performance-based bonus/allocation
• Participation in Tongston Academy sessions (scheduled periodically):
  • Personal branding (includes CV/LinkedIn review)
  • Personal finance & investing
  • Sales, communication & networking
  • Business development & strategy
  • Project management, Cybersecurity awareness & Digital automation tools.

Application Closing Date
31st August, 2026.

Hpw to Apply
Interested and qualified candidates should:
Click here to apply online

Important Information and Notice

• Where you can provide information about yourself, upload your CV & portfolio where applicable, and answer some basic pre-screening questions that demonstrate how you meet the knowledge, skills and attitude requirements for the role, in line with the JD.
• Applications will be reviewed on a rolling basis, so we strongly encourage early submission.
• If you have any questions or clarifications, please write to us at: info@tongston.com with pifhr@tongston.com in copy. Please use the subject “IC Application for – [name of the role]” in directing any correspondences to us.
• If shortlisted, you will progress through the rest of the recruitment process – technical assessment, personality & multiple intelligence check, conversation with the line manager and one or more team members, reference checks, and, if successful, an offer & if accepted, onboarding.
• Although this is a remote opportunity, candidates based in Gombe, Bauchi, Ilorin, Lagos or Abuja will be viewed favourably. For candidates who have not yet completed their NYSC, we may also be able to consider an NYSC engagement, particularly for those based in Gombe, Lagos or Abuja.