datadog
Staff Software Engineer - ML Observability
At a Glance
- Location
- United States
- Posted
- 2026-02-18T13:31:08-05:00
Key Requirements
Domain Knowledge
- Engineering
Requirements
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
You’re excited to shape the next generation of AI observability tools from the ground up
Experience with observability tools/platforms
Datadog values people from all walks of life.
Compensation & Benefits
Get to build tools for software engineers, just like yourself. And use the tools we build to accelerate our development.
Have a lot of influence on product direction and impact on the business .
Work with skilled, knowledgeable, and kind teammates who are happy to teach and learn
Competitive global benefits
Continuous professional development
Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.
Responsibilities
Drive design and implementation of LLM observability features.
Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems
Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit
Develop and extend tools for tracing, evaluating, and debugging LLMs
Influence architecture decisions and mentor engineers to build resilient, high-performance systems
Stay close to customer pain points and use those insights to guide product and engineering priorities