Principal Test Automation Engineer
$195k - $285k • Remote • Santa Clara • FullTime
Posted 2d ago
Job Location
Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
d-Matrix is seeking a Principal Test Automation Engineer to define and build AI-enabled automation across the software development lifecycle, from build and CI through testing and release. This role involves setting technical direction for AI-enabled workflow automation, building foundational components like agent harnesses and integrations, and developing evaluation methods to ensure automation effectiveness. You will work hands-on, shipping critical components and collaborating with other engineers to raise the bar for AI adoption in daily engineering tasks. The ideal candidate will have extensive production software engineering experience, strong Python skills, and experience shipping AI-enabled tools in production.
Responsibilities
- Set the technical direction for AI-enabled workflow automation across build, CI, test, and release.
- Build the shared foundation, including the agent harness and tool integrations into GitLab, Jira, test results, logs, and observability data.
- Develop evaluation methodology to measure whether an automation saves time and preserves correctness.
- Define guardrails and standards for AI autonomy and human decision-making.
- Deliver initial Quality Engineering automations, including failure attribution, defect deduplication, coverage-gap analysis, and release-readiness summaries.
- Raise the bar across engineering through shared patterns, design reviews, and mentoring.
- Determine the appropriate solution (agent, deterministic tool, or script) and teach this judgment to others.
Requirements
- Extensive production software engineering experience with strong Python skills.
- Sufficient Rust and/or C++ experience to understand build flows and diagnose compiler errors.
- Experience shipping AI-enabled tools or automation relied upon in production.
- Deep hands-on experience with LLM APIs, agent harnesses, tool integration, and context engineering.
- Experience designing evaluations for nondeterministic systems.
- Sound judgment about when AI is the right tool, including examples of choosing not to use it.
- Strong fluency across the development lifecycle, including CI/CD, testing, and release processes.
- A track record of setting technical direction across teams that do not report to you.