Ai Engineer Trainer

Key Requirements

● 2+ years in software engineering

● Strong hands-on experience in AI-augmented development workflows, LLM tooling, or agentic coding pipelines

● Must have shipped production applications using AI coding assistants such as Claude Code, Cursor, GitHub Copilot, or equivalent

● Strong full-stack background across backend APIs, frontend development, and cloud deployment

● 1+ years delivering technical software engineering or AI/ML training

● Experience coaching developers on real AI workflow integration, not only demos

● Comfortable running hands-on build labs where learners create and present working software quickly Required Technical Skills

● Claude Code: agentic coding, multi-step task orchestration, tool-use prompting, context window management, CLAUDE.md configuration

● Cursor IDE: AI-supervised development, multi-file refactoring, chat-in-editor workflows, rules-for-AI configuration, tab completion discipline

● CodeRabbit: PR review automation, custom review rules, .coderabbit.yaml config, hallucination flagging, merge gate setup

● FastAPI + SQLAlchemy + PostgreSQL: REST API design, async endpoints, Alembic migrations, connection pooling

● React + TanStack Query: component architecture, server state management, optimistic updates, error boundaries

● Docker + GitHub Actions: multi-stage Dockerfiles, 5-stage CI/CD pipelines, Render/Railway/Fly.io deployment VAYUZ Technologies | JD - AI Engineering Trainer

● Prompt Engineering: 10-component anatomy, few-shot prompting, chain-of-thought, role-based prompting, negative space prompting

● Hallucination Detection: factual, code, API, and logic hallucinations; detection heuristics; structured Missed Issues Report

● 70% Rule pedagogy: AI generates first 70%, human owns and is accountable for 100%

● AI Tool Usage Charter: personal charters and team-level AI governance policies Core Responsibilities

● Design and deliver AI Engineering Phase 1 (The Builder) across Days 1–15 of the AI Track

● Teach the full AI Engineering Pipeline: Prompt (Claude Code) → Generate (Cursor) → Audit (CodeRabbit) → Ship (Human Accountable)

● Facilitate Mini-Project 1, where each learner builds and deploys a solo application in one day

● Oversee Team Project 1, including stakeholder brief, backlog planning, sprint execution, user testing, and final presentations

● Model and enforce the 70% Rule throughout the program

● Build and maintain labs, hallucination detection exercises, daily logs, report templates, and rubrics

● Calibrate assessments including projects, reflections, daily logs, and hallucination reporting

● Keep labs and content updated in line with changes in Claude, Cursor, and CodeRabbit Preferred Profile

● Strong builder mindset with real AI-assisted engineering experience

● Able to teach practical decision-making, not just tool usage

● Passionate about preparing learners for AI-first software delivery