Staff Genai Engineer - Application Performance Monitoring (apm)

Datadog Datadog · Enterprise · Boston, MA +1 · Remote · Dev Eng

Staff GenAI Engineer focused on agentic workflows within Datadog's APM product. The role involves technical leadership in designing, training, evaluating, and deploying GenAI/ML models at scale, with a strong product mindset and collaboration across teams.

What you'd actually do

  1. Act as a technical leader within the APM organization, driving GenAI/machine learning projects from concept to production.
  2. Build and benchmark GenAI/ML models using state-of-the-art techniques.
  3. Collaborate with cross-functional teams to build automated investigation and triaging tools.
  4. Influence product direction by bringing a strong product mindset to your work, always advocating for the end user.
  5. Guide teams through ambiguity, scaling challenges, and evolving requirements with clear technical direction.

Skills

Required

  • BS/MS/PhD in a scientific field or equivalent experience
  • 10+ years of relevant engineering experience
  • experience acting as a technical lead
  • Proven track record of leading large-scale GenAI/ML initiatives in a product-driven environment
  • significant experience in model deployment, development, training, fine-tuning, or evaluation
  • Ability to drive initiatives across cross-functional teams
  • solve ambiguous challenges

Nice to have

  • deep experience in GenAI/ML
  • excellent communication skills
  • product-minded ML engineer

What the JD emphasized

  • technical leader
  • GenAI/ML projects from concept to production
  • state-of-the-art techniques
  • automated investigation and triaging tools
  • strong product mindset
  • scaling challenges
  • technical lead
  • large-scale GenAI/ML initiatives
  • product-driven environment
  • model deployment, development, training, fine-tuning, or evaluation
  • drive initiatives across cross-functional teams
  • solve ambiguous challenges

Other signals

  • agentic workflows
  • GenAI/ML models at scale
  • product-driven environment
  • model deployment, development, training, fine-tuning, or evaluation