Our client is looking for a hands-on Engineering Lead who owns its own AI Platform technical execution, architecture, code quality, and delivery across three AI abilities areas: Document AI, RAG, and Agentic AI Platform. Writes code, reviews code, and personally implements the most critical components. Must handle AI-specific non-functionals: model latency, token cost, retrieval quality, agent reliability, evaluation discipline. Collaborates with AI Research Lead on model selection and retrieval quality. What You Own: Farabi technical architecture: service decomposition, retrieval-pipeline design, agent-framework design, evaluation harness, security, deployment topology. Hands-on implementation of architecturally sensitive, performance-critical, and security-sensitive AI components. Architecture decision log: model adoption, vector-DB choice, agent-framework selection, evaluation methodology. Visible to CEO, CTO, AI Research Lead, GPM. PMEngineering loop: demand measurable acceptance c...