Requirements

• Experience in applied AI/ML engineering, graph/data systems or backend engineering for AI products.

• Strong Python and experience building APIs, data pipelines and production services.

•  Hands-on experience with LLM applications: RAG/retrieval, embeddings, function/tool calling, structured outputs, agent workflows and evaluation.

•   Strong software-engineering habits: modular code, testing, version control, observability and documentation.

•  Comfortable working with ambiguous problems and turning them into reliable, testable AI systems

•   Experience with graph databases, LangGraph or equivalent agent orchestration frameworks, conversational systems, AI observability or supply-chain/enterprise workflows is a plus.