AI Trainer

Our client is looking for a Part-Time AI Trainer to review and evaluate project submissions from students enrolled in their AI Engineer programme. This is a hands-on quality assurance and mentorship role. You will assess real projects built by learners, provide structured feedback, and help maintain the high standard the platform is known for. You are the bridge between learning and professional readiness.

Key Responsibilities

• Review student project submissions across the 12-week AI Engineer programme, evaluating each project against four grading criteria: functionality, code quality, AI integration, and originality.
• Provide detailed, written feedback on every submission — identifying what was done well, what needs improvement, and specific guidance on how to level up.
• Verify that submitted projects work end-to-end: click the link, test the product, confirm there are no critical errors before evaluating anything else.
• Assess code quality for cleanliness, organisation, and readability. Flag spaghetti code, copy-paste without understanding, and poor structure.
• Evaluate AI integration within each project. Confirm students are using AI meaningfully as a feature — chatbots, recommendation engines, content generators — not just using AI to build the project itself.
• Score originality and creative thinking. Every student receives the same brief, but the strongest submissions have a personal angle, an unexpected feature, or a problem the student genuinely cares about solving.
• Participate in calibration sessions with other trainers to ensure consistent grading standards across all reviewers.
• Flag exceptional students for potential fast-tracking into employment pipelines.
• Escalate any concerns about academic integrity, plagiarism, or students who may need additional support.
• Contribute to refining evaluation rubrics and assessment criteria as the programme evolves and new tracks are introduced.

Evaluation Framework

Every project you review is assessed on four criteria:

CriterionDescription
Functionality
Does the product work? Can you click the link and use it without errors? This is the baseline — if it does not work, nothing else matters.
Code Quality
Is the code clean, organised, and readable? No spaghetti. No copy-paste without understanding. The student must demonstrate comprehension, not just output.
AI Integration
Did the student use AI meaningfully within the product? Not just to build it, but as a feature: a chatbot, a recommendation engine, a content generator, or similar.
Originality
Did the student make it their own? The best projects always have a personal angle — a unique design choice, an unexpected feature, a problem they actually care about solving.

Requirements

• Minimum 3 years of professional software engineering experience, with proven ability to build and ship production applications.
• Hands-on experience building with AI tools and frameworks (e.g., Claude, GPT APIs, LangChain, vector databases, RAG pipelines, or similar).
• Strong code review skills — you can quickly read someone else's codebase, identify issues, and articulate clear improvements.
• Excellent written communication. Your feedback will be the primary learning mechanism for students, so clarity and constructiveness are essential.
• Familiarity with modern web development stacks , React, , Python, or equivalent).
• Self-motivated and reliable. This is a remote, part-time role — you must be able to manage your own review schedule and meet deadlines consistently.

Nice to Have

• Prior experience as a technical mentor, bootcamp instructor, or code reviewer.
• Experience with AI-native development workflows (e.g., Claude Code, Cursor, Copilot).
• Understanding of deployment pipelines and DevOps basics (Vercel, Docker, CI/CD).
• Background in technical education, curriculum design, or learning experience design.