Staff Software Engineer - ML Observability

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

Staff Software Engineer focused on building and scaling ML Observability tools for LLMs and generative AI, including drift detection, model evaluation, and behavior tracing. The role involves leading feature development, shaping product direction, and influencing architecture to ensure AI systems are observable, understandable, and reliable in production.

What you'd actually do

  1. Drive design and implementation of LLM observability features.
  2. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems
  3. Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit
  4. Develop and extend tools for tracing, evaluating, and debugging LLMs
  5. Influence architecture decisions and mentor engineers to build resilient, high-performance systems

Skills

Required

  • BS/MS/PhD in Computer Science, Engineering or related scientific field or equivalent experience
  • Deep understanding of distributed systems and scalable backend architectures
  • Hands-on experience building and shipping LLM-powered or GenAI applications.
  • Understanding of model internals, inference pipelines, evaluation techniques, and prompt engineering
  • Ability to thrive in ambiguous, fast-changing spaces and have a product-oriented mindset
  • Communicate clearly, think rigorously, and take pride in clean, maintainable code
  • Experience with observability tools/platforms

Nice to have

  • mentor engineers

What the JD emphasized

  • Hands-on experience building and shipping LLM-powered or GenAI applications.
  • Understanding of model internals, inference pipelines, evaluation techniques, and prompt engineering
  • Experience with observability tools/platforms

Other signals

  • LLM Observability
  • drift detection
  • model evaluation
  • behavior tracing
  • generative AI