Quality Engineering, Supercharged by Generative AI
What if your next role didn't just keep pace with the AI revolution — but put you at the controls? We're searching for a Senior SDET who combines battle-tested automation expertise with a genuine appetite for GenAI-powered workflows. Here, tools like Claude Code, Cursor, and the OpenAI API aren't on a roadmap — they're in your daily rotation, helping you build smarter test systems, catch defects faster, and raise the bar for what "quality" actually means.
If you've been waiting for a role where automation craft and AI innovation meet on equal footing, this is it.
How You'll Make an Impact
- Design intelligent, AI-augmented test architectures — move beyond cookie-cutter automation by leveraging generative AI to draft test scenarios, detect subtle edge cases, and accelerate root-cause analysis on failures.
- Engineer and scale Selenium WebDriver frameworks in Python, Java, or JavaScript — delivering cross-browser regression suites that are fast, deterministic, and easy to extend.
- Embed quality gates directly into CI/CD by authoring and tuning pipeline test stages in Jenkins, GitHub Actions, or Azure DevOps, so defective code never reaches production.
- Transform test telemetry into strategic insight. Query databases with SQL, parse production logs, and build dashboards (Grafana, Tableau, or similar) that track coverage, defect density, and mean time to detect — giving leadership a clear quality pulse.
- Shape what gets built, not just what gets tested. Partner with product managers and developers during design to lock down acceptance criteria and testability requirements upfront.
- Raise the bar for the team through rigorous code reviews of automation PRs, hands-on mentorship of junior engineers, and championing GenAI-assisted best practices organization-wide.
What Sets This Opportunity Apart
- AI tooling is table stakes, not a perk. Cloud resources, GenAI subscriptions, and modern CI/CD platforms are fully provisioned — spend your energy building, not requesting budget.
- Quality is a first-class engineering discipline. You're embedded with developers from sprint planning to production release — never an afterthought, always a partner.
- Ruthlessly lean processes. Documentation is concise, version-controlled, and linked to living automated checks. Heavyweight test plans have no home here.
- Every test justifies its existence. Suites are continuously refactored; flaky or redundant tests are pruned so the pipeline stays sharp and trustworthy.
What You Bring to the Table
- 5+ years of hands-on software quality experience, with a minimum of 3 years building and maintaining test automation at scale.
- Deep Selenium WebDriver knowledge — Page Object Model design, synchronization techniques, and reliable multi-browser execution.
- Production-grade coding skills in Python, Java, or JavaScript — you write framework code that other engineers can read, extend, and trust.
- Demonstrated use of GenAI tools (OpenAI API, Claude Code, Cursor, or equivalents) to solve real engineering problems — not just experimentation.
- Hands-on CI/CD experience — you've configured, debugged, and optimized automated test stages in Jenkins, GitHub Actions, or Azure DevOps.
- Strong analytical instincts — fluent in SQL, comfortable parsing structured and unstructured logs, and skilled at turning raw data into compelling visualizations.
- Effective async communication — you write clearly, present test outcomes in business terms, and collaborate seamlessly across time zones in a remote-first setup.
Nice to Have
- API testing expertise with Postman, REST Assured, or Playwright.
- Performance and load testing experience using JMeter, k6, or Locust.
- Comfort with containerized test infrastructure (Docker, Kubernetes).
- Background in security testing, accessibility compliance, or mobile automation via Appium.
- Open-source contributions in the testing or automation ecosystem.
What You'll Gain
- Frontier-level GenAI-QA skills — you'll pioneer methodologies that the broader industry is still reading blog posts about.
- End-to-end pipeline mastery across production-grade, multi-product CI/CD architectures.
- Data-driven leadership fluency — learn to forecast defect trends, build executive-facing dashboards, and influence product roadmap decisions with quality data.
- A clear trajectory forward — whether your ambition points toward Staff SDET, QA Manager, or cross-functional engineering leadership, you'll find mentorship, visibility, and real ownership to get there.
This role is for engineers who see quality as a craft worth advancing — and who want AI as their co-pilot, not a distant promise. Ready to lead from the front? Let's talk.