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Manager I, Engineering - Code Intelligence

Datadog · New York, New York, USA · On-site

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About Datadog

See metrics from all of your apps, tools & services in one place with Datadog’s cloud monitoring as a service solution. Try it for free. Backed by Index, CRV and ICONIQ.

About the role

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them.

What they're looking for

  • Experienced engineering manager with a track record of shipping products with direct customer interaction, not just internal stakeholders
  • Hands-on experience building scaled LLM software: LLM APIs, agent frameworks, prompt and eval tooling, harness and tool-use development, and closed-loop evaluation systems including LLM-as-judge
  • Strong product and customer mindset — you put solving customer problems first and know how to ship and iterate quickly
  • Comfortable setting your own product strategy in an ambiguous environment rather than executing a pre-defined roadmap
  • SDLC and developer tooling background is a plus but not required — strong AI and agent experience is what matters most
More about this role

Code Intelligence sits at the intersection of agentic engineering and product, running agents against real customer source code in production. This is a chance to own an AI-native team at the center of a business-critical growth area. High visibility, high leverage, and squarely in the fastest-growing part of the AI agent space.

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them.

  • Lead and develop an existing engineering team, building trust, setting technical direction, and establishing a high bar for ownership and execution.
  • Own the roadmap and execution across four areas: source code indexing, PR Agentic Reviewers (agents that generate artifacts like metric descriptions on customer pull requests), shift-left work (extending code-writing agents to make direct changes to customer repos), and closed-loop feedback and evaluation systems including LLM-as-judge.
  • Set the team's product strategy independently while partnering day-to-day with product teams company-wide — this team...

Read the full posting on Datadog's site ↗

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