Senior Software Engineer Databricks AI

Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.

Series F+0 current maintainers0 active leads
160 Spear Street, Suite 1300, San Francisco, CA 94105, United States
About Databricks

Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.

View jobs by Databricks

Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will design and build backend systems for an MLOps and LLMOps platform, taking services from design through production. You will develop scalable APIs, ingest and query traces, metrics, and artifacts, build evaluation and monitoring capabilities, optimize platform cost and scalability, and establish engineering best practices.

Requirements

  • BS or higher in Computer Science or a related field
  • 5+ years of experience developing large-scale distributed systems, scaling infrastructure, or building platforms and developer tools
  • Strong foundation in algorithms, data structures, and system design
  • Experience with backend stacks such as Scala or Java
  • Experience with AWS, Azure, GCP, Docker, or Kubernetes
  • Engineering maturity in security, correctness, and operational excellence
  • Strong communication and cross-team collaboration skills

Responsibilities

  • Design and implement scalable, reliable core services and APIs
  • Build systems to ingest, store, and query traces, metrics, and artifacts
  • Develop evaluation and monitoring capabilities for AI agents
  • Optimize platform scalability and cost across customers and cloud regions
  • Collaborate with product, research, and customers on product direction
  • Establish code quality, testing, and operational-readiness practices
  • Mentor engineers