Senior Software Engineer, Data Center Infrastructure Tooling

Weights & Biases Weights & Biases · Data AI · Bellevue, WA +4 · Remote · Technology

Senior Backend Engineer to build in-house tooling for managing AI data center infrastructure, focusing on data models, APIs, and operational aspects. The role involves designing and implementing a high-performance internal platform to model physical and logical infrastructure for planning, coordination, and automation.

What you'd actually do

  1. Data models and APIs that capture the complexity of datacenter infrastructure: devices, connectivity, cabling, power, cooling, and spatial relationships across racks, rows, and floors. The schema needs to be expressive enough to model reality and performant enough to query at scale.
  2. High-throughput API services in Go (gRPC, GraphQL, and/or REST) that support the data density and interaction speed the frontend demands, including complex filtering, aggregation, and bulk operations across large datasets.
  3. The backend architecture from the ground up: service structure, data access patterns, caching strategy, and API contracts designed to scale with the team and product scope.
  4. Integrations with internal/external systems and data sources that feed infrastructure planning, ensuring the platform reflects real-world state and planned builds accurately.
  5. Deployment and operational infrastructure for the services you build, including Kubernetes manifests, CI/CD pipelines, observability, and reliability practices.

Skills

Required

  • Go
  • PostgreSQL
  • CockroachDB
  • API design (gRPC, GraphQL, REST)
  • performance optimization
  • Kubernetes
  • CI/CD
  • monitoring
  • alerting
  • incident response
  • data modeling
  • backend engineering

Nice to have

  • datacenter operations
  • infrastructure planning
  • DCIM tools (NetBox, Infrahub, Sunbird)
  • CockroachDB specifically

What the JD emphasized

  • understanding where bottlenecks actually live rather than where you assume they are.