Software Engineer - Testing Frameworks

ABOUT BASETEN

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.

THE ROLE

Baseten is seeking talented and experienced Software Engineers to join our Platform team within the Infrastructure organization. As a senior member of Baseten's Platform Team, you will own the systems that let every engineer at Baseten prove their code works before it reaches production. Our product runs mission-critical AI inference for customers who measure downtime in dollars per second, which means our internal bar for correctness, performance, and failure tolerance has to be exceptional.

Your focus is the full testing stack: fast and reliable unit test tooling, integration harnesses that spin up realistic environments on demand, load and performance testing for GPU-backed inference workloads, and resilience testing that deliberately breaks things so our customers never have to find out what happens when a node dies mid-request. This is a builder role with org-wide leverage. You won't be writing tests for other teams — you'll be building the frameworks, harnesses, and feedback loops that make writing good tests the path of least resistance, and you'll set the standards for what "well-tested" means at Baseten.

RESPONSIBILITIES

Own Baseten's testing strategy end to end — define the standards, the tiers, and the tooling that engineering teams build against.

Build and maintain unit, integration, load and performance testing frameworks

Design end to end test infrastructure that provisions realistic dependencies on demand — ephemeral Kubernetes namespaces, containerized service dependencies, etc.

Build resilience and chaos testing capabilities: fault injection, network partition and latency simulation, pod and node failure scenarios, dependency degradation, and automated verification that our systems degrade gracefully and recover.

Attack test suite reliability head-on — flake detection and quarantine, test impact analysis and selective execution, parallelization, and aggressive reduction of end-to-end CI wall time.

Build observability into the testing layer itself: coverage reporting, test health dashboards, failure triage tooling, and clear signals about which areas of the codebase are under-tested.

Create project templates and shared libraries so new services start with a complete testing setup on day one.

Partner directly with product and infrastructure teams — embed where needed, understand their hardest testing problems, and turn one-off solutions into platform capabilities.

Mentor engineers across the org on testing practice and raise the collective bar through code review, documentation, and internal advocacy.

REQUIREMENTS

Strong proficiency in Go and/or Python, with hands-on experience building test tooling and libraries used by other engineers.

Deep experience with testing frameworks and their internals — pytest, Go's testing package, testify, testcontainers, or equivalents — including the ability to extend them, not just use them.

Experience designing integration test infrastructure for distributed systems, including ephemeral environment provisioning and dependency management.

Practical experience with load and performance testing tools (k6, Locust, Vegeta, JMeter, Gatling, or similar) and the judgment to interpret results and drive action from them.

Solid Kubernetes and Docker fundamentals — you can build test infrastructure that runs on and tests against real cluster environments.

Advanced understanding of CI/CD, including how to keep large test suites fast, deterministic, and trustworthy at scale.

A track record of measurably improving testing culture on an engineering team — you have opinions on what to test, what not to test, and where the ROI actually is.

Are excited about building foundational infrastructure and are comfortable working independently on ambiguous, high-impact technical challenges