As a Staff SDET, You Will

• Define and lead the vision for test automation architecture and quality engineering at scale.
• Design, build, and evolve reusable test frameworks that are maintainable, scalable, and efficient.
• Collaborate with Engineering, Product, and DevOps to embed testing throughout CI/CD and cloud-based deployments.
• Guide architectural decisions to improve testability, observability, and long-term system health.
• Identify and resolve quality gaps, technical debt, and inefficiencies across teams.
• Mentor developers, SDETs, and QA team members to build testing skills and promote a quality-first mindset.
• Standardize tools and technologies that support test automation and improve development workflows.
• Monitor and report on testing coverage, quality KPIs, and risk areas to inform planning and continuous improvement.
• Champion AI-assisted development across the org, piloting and standardizing tools that accelerate test authoring, triage, results analysis, and code review.
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Qualifications, Skills, And Competencies

At Safe Software, we welcome diverse backgrounds and experiences. While not all candidates will have everything listed, the most successful candidates will bring many of the following:

What We’re Looking For

• 8+ years of experience in software development or test automation, including roles with technical leadership scope.
• Advanced skills in programming languages such as Python, Java, or C++.
• Deep experience with testing frameworks like Pytest, Selenium, or custom solutions.
• Strong knowledge of CI/CD and orchestration tools (e.g., Jenkins, GitHub Actions, Docker, Kubernetes).
• Experience with infrastructure-as-code, systems-level testing, and test infrastructure at scale.
• Proven ability to influence cross-team testing strategies and mentor engineers across experience levels.
• Strong communication and leadership skills, with a collaborative and inclusive approach.
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Nice To Have

• Hands-on experience testing AI/ML or LLM-powered features, including building evaluation frameworks and dealing with non-deterministic outputs.
• Practical fluency with AI coding assistants and agentic dev tools (Claude Code, Copilot, Cursor, etc.) and a point of view on how to use them safely and effectively in a quality engineering context.
• Experience integrating AI capabilities into developer tooling or test infrastructure (e.g., AI-driven flake detection, auto-triage, self-healing tests).
• Experience scaling test practices in hybrid or cloud-native environments.
• Familiarity with performance profiling, observability tooling, or resilience testing.
• Involvement in community-of-practice leadership or internal quality initiatives.
• Passion for continuous improvement and innovation in test automation and engineering practices.