[Hiring] Staff AI Engineer - MCP Services @Datadog

Role Description

Datadog’s MCP team is scaling the capabilities of our MCP Services — an interface that enables external agents like Claude and Cursor, as well as internal Datadog AI Agents, to interact with Datadog data. As a Staff Engineer, you’ll play a critical role in evolving this agent-friendly tool surface, enabling agentic workflows across metrics, logs, and incidents etc. You'll drive forward advanced evaluation frameworks for agentic systems and contribute to the next generation of agent-tool interaction models. This is a fast-evolving space with deep ambiguity and high impact — ideal for someone eager to help shape Datadog’s applied AI future.

What You’ll Do:

• 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

Qualifications

• 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

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
• Friendly and inclusive workplace culture