Senior Software Engineer - Bits AI Sre

Datadog Datadog · Enterprise · Boston, MA +2 · Remote · Dev Eng

Senior Software Engineer to build AI-assisted product experiences for Datadog customers, focusing on conversational workflows, guided remediations, and codefixes. The role involves backend engineering, product development, and prompt engineering for reliable, production-quality AI systems.

What you'd actually do

  1. Work closely with product managers, designers, and engineers to build and iterate on AI-powered product experiences in Bits AI SRE.
  2. Develop customer-facing systems across chat, remediations, and codefixes that help users resolve production issues more quickly.
  3. Work on prompts, evaluation loops, and backend systems to make applied AI workflows reliable, useful, and production-ready.
  4. Prototype quickly, test what works in the real world, and iterate rapidly to ship new product capabilities.
  5. Build the infrastructure and product logic needed to connect AI outputs to meaningful actions, including operational remediations and generated code changes.

Skills

Required

  • backend engineering
  • product mindset
  • Go (or similar)
  • LLM-based systems
  • prompt engineering
  • evaluation
  • iteration for LLM-powered systems
  • productionizing AI features
  • integrating model behavior into reliable user-facing products
  • AI coding tools

Nice to have

  • Kubernetes
  • systems related to production remediation
  • operational automation
  • push the boundaries of how AI can improve software engineering best practices
  • building AI-enabled products

What the JD emphasized

  • at least 5 years of professional experience
  • strong backend engineering skills
  • product mindset
  • experience building production systems in Go (or similar)
  • worked with LLM-based systems in practice
  • experience with prompt engineering, evaluation, and iteration for LLM-powered systems
  • strong engineering fundamentals
  • build the systems needed to productionize AI features
  • integrating model behavior into reliable user-facing products
  • Demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output

Other signals

  • building AI-assisted product experiences
  • applied AI
  • production-quality AI systems
  • LLM-based systems