Build and own the testing frameworks, integration environments, performance tooling, and resilience capabilities that enable reliable AI inference infrastructure. The role requires strong Go or Python skills, distributed-systems testing experience, Kubernetes and Docker expertise, and the ability to improve test reliability at scale.
165k – 330k/yr
Hybrid5+ YOEQA Engineering
About the role
Responsibilities
Own Baseten's testing strategy end to end, including standards, tiers, and tooling.
Build and maintain unit, integration, load, and performance testing frameworks.
Design end-to-end test infrastructure that provisions realistic dependencies on demand, including ephemeral Kubernetes namespaces and containerized service dependencies.
Build resilience and chaos testing capabilities, including fault injection, network partition and latency simulation, pod and node failure scenarios, dependency degradation, and automated recovery verification.
Improve test-suite reliability through flake detection and quarantine, test impact analysis, selective execution, parallelization, and reduced CI wall time.
Build observability into the testing layer, including coverage reporting, test-health dashboards, failure-triage tooling, and signals identifying under-tested code.
Create project templates and shared libraries so new services start with complete testing setups.
Partner with product and infrastructure teams to turn one-off testing solutions into platform capabilities.
Mentor engineers through code review, documentation, and internal advocacy.
Requirements
Strong proficiency in Go and/or Python, with experience building test tooling and libraries for other engineers.
Deep experience with testing frameworks and their internals, including pytest, Go's testing package, testify, testcontainers, or equivalents.
Experience designing integration-test infrastructure for distributed systems, including ephemeral-environment provisioning and dependency management.
Practical experience with load and performance-testing tools such as k6, Locust, Vegeta, JMeter, or Gatling.
Solid Kubernetes and Docker fundamentals.
Advanced understanding of CI/CD and large-scale test-suite optimization.
A track record of measurably improving testing practices and culture on an engineering team.
Comfort working independently on ambiguous, high-impact infrastructure challenges.
Compensation and Benefits
Competitive compensation, including meaningful equity.
100% coverage of medical, dental, and vision insurance for employees and dependents.
Flexible paid time off and company-wide Winter Break.
Paid parental leave.
Fertility and family-building stipend through Carrot.
Company-facilitated 401(k).
Exposure to a variety of machine-learning startups.
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