
GenAI Engineering Lead
5 days ago
About The Role:
This is a hands-on leadership role. You'll lead GenAI system development, mentor engineers (including MLOps), and grow a high-impact team.
What You'll Do:
- 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
Basic Requirements
- 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
Why Honeycomb?
- 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
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