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Staff Applied Scientist - Agentic Interfaces

Datadog· Engineering
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New York$276k - $345kfull-timePosted 4mo ago

About the role

Staff Applied Scientist to define evaluation metrics and build measurement systems for Datadog's AI agent integrations, driving end-to-end evaluation of agent data interactions and ensuring improvements in retrieval relevance, tool selection, and context efficiency across first- and third-party agents.

Responsibilities

  • Own the evaluation strategy for Datadog's AI agent integrations. Define the metrics — offline and online, quality and cost, single-turn and trajectory-level — that the team and the broader organization optimize against.
  • Build the eval datasets, golden traces, and regression harnesses that catch quality changes before they hit customers, and make those assets reusable by every team contributing tools to the platform.
  • Drive measurable improvements to retrieval relevance, tool-selection accuracy, and context efficiency, partnering closely with the AI engineers on the team who build the underlying platform.
  • Run applied research on the open problems in agent–data interaction: tool selection under large catalogs, multi-turn agent evaluation, grounding and hallucination control on live telemetry, cost/quality tradeoffs at scale.
  • Partner with the Bits SRE, Bits Assistant, and Bits Dev Agent teams so first-party agents benefit from the same measurement substrate as third-party integrations, and so learnings move freely in both directions.
  • Provide technical leadership across the Agentic Interfaces team and the broader organization through design reviews, working groups, and mentorship, and represent the team externally through talks, blog posts, and contributions to the open agent ecosystem.

Qualifications

  • You have a BS/MS/PhD in a scientific field, or equivalent experience.
  • 10+ years of relevant engineering or applied science experience, including time as a technical lead.
  • Proven track record of leading ML or GenAI initiatives in a product-driven environment, from research through production.
  • Significant experience with evaluation, experimentation, or measurement of ML systems at scale.
  • You bring a strong product mindset and are comfortable driving initiatives across cross-functional teams.
  • You thrive in ambiguity and can make sound technical calls when the path isn’t yet defined.

Skills

Required:Evaluation strategyDataset and benchmark designML system evaluation at scaleCross-functional leadership

Benefits

  • New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
  • Continuous professional development, product training, and career pathing
  • An inclusive company culture, giving programs, and the ability to join our Community Guilds (Datadog employee resource groups)
  • Competitive global benefits and global Spring Health benefits for employees and dependents age 6+
Last updated Oct 22, 2026. Interested? Apply on the company site.

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