Senior GenAI Data Scientist

 About The Role:

As a Senior GenAI Data Scientist, you will architect, develop, and deploy advanced GenAI systems that power mission-critical workflows across Honeycomb. You’ll work closely with engineering, product, and business leaders to build scalable agentic systems, robust RAG pipelines, and high-reliability LLM infrastructure—ultimately accelerating the company’s AI transformation.

This is a high-ownership role where your work directly influences our products, operations, and long-term AI strategy.

 

What You’ll Do: 

• Design, develop, and ship advanced agentic workflows and GenAI applications end-to-end
  
  
• Build, optimize, and productionize RAG pipelines for grounding LLMs in insurance-specific data
  
  
• Integrate LLM agents with APIs, policy/claims systems, and internal business tools
  
  
• Own technical solutions for LLM evaluation, observability, versioning, safety, and error handling

 

Requirements

• Master’s degree or PhD in Computer Science, Machine Learning, Statistics, Engineering, or a related field
  
  
• 6+ years total experience in AI/ML or Data Science
  
  
• 3+ years hands-on building and deploying GenAI applications (LLMs, agents, RAG, etc.)
  
  
• Strong hands-on experience with LLM agents, including multi-agent orchestration, tool use, planning/reasoning, and context-managed conversational systems (e.g., LangGraph, HF Transformers Agents, OpenAI Agents)
  
  
• Deep expertise in Retrieval-Augmented Generation, vector databases, embedding model selection, and retrieval optimization
  
  
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, scikit-learn, or Hugging Face
  
  
• Strong NLP and transformer-model knowledge with a track record of applying LLMs to real-world use cases
  
  
• Strategic, product-oriented mindset with the ability to map AI capabilities to business opportunities
  
  
• Highly self-driven, curious, and comfortable solving complex problems independently
  
  

• Experience in regulated domains (insurance, finance), knowledge graphs, or agent observability - an advantage 
  
  
• Familiarity with modern tuning and optimization techniques (PEDFT, LoRA/QLoRA, PPO, GRPO, etc.) - an advantage  

 

Why Honeycomb

• Build foundational AI systems in a sector ripe for innovation and modernization
  
  
• See your work deployed quickly with immediate customer and business impact
  
  
• Collaborate directly with product, engineering, and executive teams—minimal bureaucracy
  
  
• High autonomy, fast development cycles, and meaningful equity ownership
  
  
• Be part of a mission-driven company redefining what insurance technology can be