Staff Engineer, AI/LLM Platform

• Agent Systems and Product Surfaces
  • Help design, build, and distribute the agentic systems that surface our scientific capability to customers
  • Build agent loops, orchestration code, and control structures that balance autonomy, cost, and latency
  • Make day-to-day decisions on prompts, tools, structured outputs, and provider tradeoffs across Anthropic, OpenAI, and others
• Context, Knowledge and MCP Layer
  • Build and operate MCP servers that expose our core scientific engines and product capabilities to agentic clients
  • Design and maintain the context-management layer that feeds agents the right information at the right time
  • Stand up vector stores, knowledge bases, and retrieval patterns that power both agent reasoning and customer-facing workflows
• Quality & Team Impact
  • Build the evals, traces, and feedback loops needed to debug and improve a non-deterministic system
  • Contribute to the architectural patterns and technical standards the team builds on
  • Mentor engineers contributing to AI features and raise the floor on applied-AI practice across the team
• Other Duties as Assigned

• 5+ years of professional software engineering experience, with recent production work on agents, LLM-integrated features, or MCP and tool servers
• Strong Node.js and TypeScript background; comfort designing service-layer code and tool integrations
• Working knowledge of agent orchestration, prompt and tool design, and context-management patterns (RAG, vector search, memory)
• Hands-on experience with at least one major LLM provider SDK (Anthropic, OpenAI, or comparable)
• Pragmatic, applied mindset — this is an engineering role, not a research or data-science role
• Fluency using AI coding tools (Claude, Cursor, Copilot) in daily workflow, and comfort working across languages by leveraging them

• Python proficiency for prototyping, evals, or interfacing with ML tooling
• Experience with agent frameworks such as LangGraph, Mastra, Pydantic AI, or LlamaIndex — with the judgment to know when not to use them
• Familiarity with vector databases and RAG patterns (Pinecone, pgvector, MongoDB Atlas Vector Search, or comparable)
• Experience in regulated-software environments (SOC 2, HIPAA, GxP, 21 CFR Part 11) or life-sciences SaaS
• Open-source contributions to MCP servers, agent frameworks, or LLM tooling

• Bachelor's degree in computer science, engineering, or related field preferred
• Master’s degree in computer science, engineering or related field a plus
• Relevant technical certifications welcomed

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