GenAI Engineering Lead

At Honeycomb, we're not just building technology , we’re reshaping the future of insurance.

In 2025, Honeycomb was ranked by Newsweek as one of “America’s Greatest Startup Workplaces,” and Calcalist named it as a “Top 50 Israel startup.”

How did we earn these honors?

Honeycomb is a rapidly growing global startup, generously backed by top-tier investors and powered by an exceptional team of thinkers, builders, and problem-solvers. Dual-headquartered in Chicago and Tel Aviv (R&D center), and with 5 offices across the U.S., we are reinventing the commercial real estate insurance industry, an industry long overdue for disruption. Just as importantly, we ensure every employee feels deeply connected to our mission and one another.

With over $55B in insured assets, Honeycomb operates across 18 major states, covering 60% of the U.S. population and increasing its coverage.

If you’re looking for a place where innovation is celebrated, culture actually means something, and smart people challenge you to be better every day - Honeycomb might be exactly what you’ve been looking for.

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
  
  

• 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