Example Company
Software engineer
- Location
- San Francisco
- Type
- Full time
- Compensation
- $150k-$200k
- Posted
- 2 days ago
Join a team building useful software. Work closely with engineering and design to turn new ideas into products.
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QA Engineer
- Location
- San Francisco
- Type
- Full time
- Posted
- 19D AGO
About the role
QA Engineer
San Francisco In-PersonFull-timeREAD MOREWe're hiring our first QA engineer. Customers operate their GPU fleets through @aranya, our Slack interface, and NEO, our revolutionary AI-native GUI. When someone asks @aranya to upgrade a cluster, it has to understand them, do the right thing, and never break production. You'll own quality, e2e, and integration testing across both interfaces and bring your experience to become the authority on the art and practice of product quality at Aranya!
What You'll Do- Test @aranya end to end: conversation flows, command accuracy, and the actions it takes on real clusters
- Build evals for agent behavior: correct answers, safe actions, sane handling of ambiguous or bad requests
- Build end-to-end tests for NEO as it ships
- Verify NEO and @aranya behave consistently: same engine underneath, so the same request should get
the same result - Write integration tests in Go for the multicluster backend behind both: install, upgrade, failover
- Spin up and tear down Kubernetes test clusters on demand, and validate controllers, operators, and CRDs
against real cluster behavior across Kubernetes versions - Verify alerting: alerts fire when they should, reach Slack and the UI, and only then
- Gate releases in CI; turn bugs and incidents into regression tests
What We're Looking For- 3+ years in QA, SDET, or test automation
- Golang, Kubernetes, React, RPC (gRPC or similar)
- CI/CD (GitHub Actions or similar)
- Linux fundamentals
- End-to-end testing of web UIs
Nice to Have- Alerting and monitoring: Prometheus, Alertmanager, Grafana
- Multicluster tooling: Cluster API, Argo CD, Flux
- Chaos engineering tools
- Kubernetes testing tools
- GitOps workflows (Argo CD, Flux) or infrastructure-as-code tooling
- Experience as the first QA hire at an early-stage company
- Testing LLM-powered or conversational products, including evals
- Slack apps or bots
- Playwright or similar UI test frameworks
The past generation saw the rise of personal computing. This generation, we will see the advent of the personal
cluster. Aranya is the multicluster operating system for GPU infrastructure: it provisions, heals, and upgrades
entire fleets of bare metal Kubernetes clusters, so any team can run AI at scale without hiring a platform
engineering team. Leading AI inference companies already run their production fleets on it.
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