Principal Test Automation Engineer

d-Matrix • Santa Clara, CA

1d • $195,000 - $285,000

About The Position

d-Matrix is hiring a Principal Software Engineer to define and build AI-enabled automation across the software development lifecycle, from build and CI through testing and release. The codebase spans a kernel compiler, firmware, device drivers, and an inference serving stack running on company-designed silicon. Testing involves real hardware, numerical correctness, and failures that can originate across multiple layers.

The role sets technical direction for AI-enabled workflow automation and builds shared foundations, including an agent harness, integrations with GitLab, Jira, test results, logs, and observability data, as well as guardrails and evaluation methods. The engineer will remain hands-on, deliver complex automation, collaborate with a Senior/Staff engineer in the same area, and improve how the broader engineering organization uses AI in its daily work.

Requirements

• Extensive production software engineering experience and strong Python skills.
• Enough Rust and/or C++ experience to understand build flows and diagnose compiler errors.
• Experience shipping AI-enabled tools or automation that others relied on in production, beyond demos.
• Deep hands-on experience with LLM APIs, agent harnesses, tool integration, and context engineering.
• Experience designing evaluations for nondeterministic systems that demonstrate an automation helped without causing other problems.
• Sound judgment about when AI is appropriate, 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.

Nice To Haves

• Exposure to compilers, firmware, or hardware-in-the-loop test environments.
• Experience building tool integrations with MCP or similar protocols.
• Experience working with GitLab, Jira, or Prometheus APIs.
• Experience managing cost and latency in LLM-based systems.
• Daily use of AI coding tools such as Claude Code, Cursor, or Copilot, with well-formed opinions on where they help and where they do not.

Responsibilities

• Set technical direction for AI-enabled workflow automation across build, CI, testing, and release.
• Build shared foundations, including the agent harness and integrations with GitLab, Jira, test results, logs, and observability data.
• Develop evaluation methods to measure whether automation saves time while preserving correctness.
• Define guardrails and standards for autonomous AI actions, human review, and auditable changes.
• Deliver initial Quality Engineering automations for cross-layer failure attribution, failure clustering and defect deduplication, coverage-gap analysis, and release-readiness summaries.
• Establish shared patterns, participate in design reviews, and mentor engineers to raise the bar across the organization.
• Determine when to use an agent, a deterministic tool with a narrow model step, or a simple script, and teach that judgment to others.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed