Staff ML Engineer — LLM/RAG Systems

About the role

What you’ll be doing

Join our AI Practice as a Staff ML Engineer building production LLM and retrieval-augmented generation systems for enterprise clients. You'll architect and ship AI agents, document intelligence pipelines, and evaluation frameworks that create measurable business value — not demos that never leave the sandbox.

• Architect and build production RAG pipelines, AI agents, and LLM-powered workflows
• Design retrieval strategies, chunking approaches, and vector store architectures for scale
• Own model evaluation, prompt engineering, and fine-tuning where applicable
• Set technical direction for the AI Practice's engineering standards and tooling
• Partner with clients on responsible AI practices, bias auditing, and enterprise security requirements
• Optimize inference cost, latency, and reliability for production LLM systems
• Mentor ML engineers and review architecture proposals across engagements

• 7+ years in ML/software engineering, with 2+ years building production LLM/RAG systems
• Deep hands-on experience with LangChain, vector databases (Pinecone or similar), and embedding models
• Strong Python engineering skills and experience with frameworks like FastAPI
• Track record shipping AI systems that survived contact with real production traffic
• Familiarity with responsible AI practices: bias auditing, guardrails, evaluation harnesses
• Experience with MLOps tooling (MLflow or equivalent) for tracking and reproducibility
• Excellent communication skills for explaining AI system tradeoffs to non-technical stakeholders