Knowledge Base (KB) Reviewer & AI Output Tester at Tongston Entrepreneurship Group - Remote

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.

We are recruiting to fill the position below:

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.