Ai Engineer • Staff

Who you are

You have extensive experience in AI engineering, particularly in developing systems that facilitate interaction between intelligent agents and data. Your background includes designing and implementing agentic tool surfaces tailored for evaluation and production use across various AI agents. You thrive in fast-evolving environments and are eager to shape the future of applied AI at Datadog.

You possess strong analytical skills, enabling you to investigate and resolve failure cases by analyzing tool output and improving query parsing. Your collaborative spirit allows you to work effectively across Applied AI and internal teams, aligning on shared standards for tool integration and data access. You are comfortable navigating ambiguity and are driven by the impact of your work.

What you'll do

As a Staff AI Engineer, you will lead efforts to improve Datadog’s public-facing MCP server, enabling intelligent agents to discover and interact with our services. You will design and implement advanced evaluation pipelines for measuring agent performance on Datadog workflows, such as investigations, incident triage, and metric queries. Your role will involve collaborating with various teams to ensure seamless integration of tools and data access standards.

You will also be responsible for driving forward advanced evaluation frameworks for agentic systems, contributing to the next generation of agent-tool interaction models. Your work will have a significant impact on how agents interact with Datadog data, shaping the future of our applied AI capabilities.

What we offer

At Datadog, we value our office culture and the relationships built within our teams. We operate as a hybrid workplace, allowing you to create a work-life harmony that best fits your needs. You will be part of a dynamic team that encourages collaboration and creativity, contributing to a fast-evolving space with deep ambiguity and high impact. We encourage you to apply even if your experience doesn't match every requirement, as we believe diverse teams build better products.