Job description

Build and operate the distributed systems that ingest, store and query telemetry at the scale our customers actually run. What you’ll work on • Build and operate distributed systems that ingest, store and query telemetry at scale: metrics, logs, traces, RUM and profiles. • Make high-cardinality data fast and affordable through compression, downsampling, tiering and tenant isolation. • Work across the stack we run in production: Go, Java, Kafka, Pinot, Kubernetes. What we look for • Strong, recent, hands-on experience building large-scale distributed systems. • Depth in the fundamentals. • Generalists who move across the system rather than staying in one lane. • Engineers who operate what they build and treat reliability as part of the job. • Comfort owning ambiguous problems end to end, from design through production. Bonus • Prior work in observability, APM or monitoring. • Time-series or columnar storage internals: encodings, compression, cache behaviour. How we work • Small team, short feedback loops, real ownership from week one. • You’ll talk to customers, engineers debugging real incidents, and that shapes what you build. • We ship, then iterate; bias toward hands-on building over process. • Modern tooling is encouraged, including AI-assisted development.

Requirements

Must-haves

Build and operate the distributed systems that ingest, store and query telemetry at the scale our customers actually run.
What you’ll work on
Build and operate distributed systems that ingest, store and query telemetry at scale: metrics, logs, traces, RUM and profiles.
Make high-cardinality data fast and affordable through compression, downsampling, tiering and tenant isolation.
Work across the stack we run in production: Go, Java, Kafka, Pinot, Kubernetes.
What we look for
Strong, recent, hands-on experience building large-scale distributed systems.
Depth in the fundamentals.
Generalists who move across the system rather than staying in one lane.
Engineers who operate what they build and treat reliability as part of the job.
Comfort owning ambiguous problems end to end, from design through production.

Nice-to-haves

Prior work in observability, APM or monitoring.
Time-series or columnar storage internals: encodings, compression, cache behaviour.
Small team, short feedback loops, real ownership from week one.
You’ll talk to customers, engineers debugging real incidents, and that shapes what you build.
We ship, then iterate; bias toward hands-on building over process.
Modern tooling is encouraged, including AI-assisted development.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

gojavakubernetesai

Platform: careers-html
Effort: medium