Staff Engineer, AI/LLM Platform

Location

• Remote

Job Responsibilities

• 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
• 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
• 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
• 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

Required Qualifications

• 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

Preferred Qualifications

• 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

Education