24 days ago
Base Salary
$195k - $285k/yr
Responsibilities
- Set technical direction for AI-enabled workflow automation across build, CI, testing, and release.
- Build shared agent infrastructure and integrations with GitLab, Jira, test results, logs, and observability data.
- Develop evaluation methods to measure automation effectiveness, time savings, and correctness preservation.
- Define guardrails, standards, and auditability practices for autonomous and human-reviewed AI actions.
- Deliver quality-engineering automations for cross-layer failure attribution, failure clustering, defect deduplication, coverage-gap analysis, and release-readiness summaries.
- Provide technical direction through shared patterns, design reviews, mentoring, and organization-wide guidance.
- Choose appropriately among agents, deterministic tools, narrow model steps, and scripts.
Requirements
- Extensive production software engineering experience with strong Python skills.
- Experience with Rust and/or C++ sufficient to understand build flows and diagnose compiler errors.
- Experience shipping production AI-enabled tools or automation relied upon by others.
- Deep hands-on experience with LLM APIs, agent harnesses, tool integration, and context engineering.
- Experience designing evaluations for nondeterministic systems.
- Strong fluency across software development, CI/CD, testing, and release processes.
- Track record of setting technical direction across teams without direct reporting authority.
- Preferred experience includes compilers, firmware, hardware-in-the-loop testing, MCP or similar protocols, GitLab, Jira, Prometheus APIs, and cost and latency management for LLM systems.
- Daily experience with AI coding tools such as Claude Code, Cursor, or Copilot is preferred.
Categories
About d-Matrix
d-Matrix builds AI inference computing platforms for data centers, combining custom silicon with systems, networking, and software. Its flagship Corsair platform and JetStream fabric focus on low-latency, energy-efficient generative AI inference at scale. Founded in 2019 and headquartered in Santa Clara, California, the privately held company sells hardware with accompanying software to cloud providers and enterprises deploying large AI models.