Lead, AI Engineering
bain
Job Description
- Design and develop GenAI applications (e.g., copilots, workflow automation, decision support) using modern LLM stacks.
- Implement agentic workflows where they add clear value (e.g., tool use, multi-step execution, human-in-the-loop controls), with attention to reliability, safety, and clear failure modes.
- Design and build advanced search, retrieval, and knowledge pipelines across diverse data structures and stores (e.g., hybrid search, vector stores, graph databases/knowledge graphs, and traditional data platforms), covering indexing strategies, metadata design, relevance tuning/reranking, freshness, caching, access controls, and source attribution.
- Build robust agent capabilities including context engineering, memory/state management (short-term and long-term), orchestration, routing, and tool integration patterns.
- Integrate solutions into enterprise environments and workflows (APIs, data systems, collaboration tools), balancing quality, latency, cost, privacy, and adoption.
- Translate ambiguous client needs into clear technical requirements, tradeoffs, and delivery plans.