Lead GenAI Engineer

• Architect and ship production-grade agentic workflows (LangChain, LlamaIndex, CrewAI, LangGraph)
• Build RAG pipelines that ground LLMs in structured and unstructured insurance data
• Connect LLM agents to internal APIs, claims/policy databases, and support tools
• Collaborate with MLOps engineers using Modal and graph-based orchestration to scale reliable inference
• Define best practices for LLM evaluation, observability, prompt/tool versioning, and error handling
• Lead technical direction, mentor team members, and help scale Honeycomb's GenAI footprint
• Working with the SLT in deploying AI across the organization for operational excellence

• 6+ years backend/systems experience (Python preferred), with real-world GenAI applications
• Deep hands-on with LLM frameworks (LangChain, CrewAI, RAG, vector DBs)
• Understanding of agentic workflows, tool-calling, memory, and task decomposition
• Experience with inference orchestration tools (Modal, Ray, etc.) and vector-based retrieval
• Strong mentorship skills and interest in growing a GenAI team
• Familiarity with Knowledge Graphs, agent observability, or regulated domains like insurance/finance - an advantage

• Lead the GenAI strategy and execution at a company transforming a legacy industry
• Build high-leverage AI systems with immediate customer and business impact
• Work directly with product, underwriting, and execs - no bureaucracy
• High ownership, fast cycles, meaningful equity

Mploy