Experienced Staff-level engineer with a strong background in applied AI, agentic programming, and/or the following: LLM-powered automation pipelines, LLM orchestration frameworks (e.g., LangChain, LangGraph, CrewAI), Agent orchestration and tool-use systems
Comfortable working in high ambiguity and fast-changing environments; able to define and prioritize direction autonomously
Skilled in building evaluation frameworks for LLM agents or AI systems, including metrics design and data instrumentation
Bonus: Experience working with the MCP standard or contributing to agent-compatible tooling surfaces, familiarity with building and evaluating ReAct agentic loops
Strong systems thinking, able to reason across multiple agents, tools, and user scenarios
Passionate about pushing boundaries in agent-augmented software and eager to shape evolving interfaces
What You'll Be Doing:
Lead efforts to improve Datadog’s public-facing MCP server, enabling intelligent agents to discover and interact with our services
Design and implement agentic tool surfaces tailored for evaluation and production use across a wide variety of AI agents
Build and maintain advanced evaluation pipelines for measuring agent performance on Datadog workflows (e.g., investigations, incident triage, metric queries)
Investigate and resolve failure cases by analyzing tool output, improving query parsing, and enhancing agent feedback mechanisms
Collaborate across Applied AI and internal teams to align on shared standards for tool integration and data access
Perks and Benefits:
Generous and competitive benefits package
New hire stock equity (RSUs) and employee stock purchase plan
Continuous career development and pathing opportunities
Employee-focused best in class onboarding
Internal mentor and cross-departmental buddy program