Staff Software Engineer in Test, Compiler & Systems Validation

Code Metal develops automated, verifiable software engineering solutions for code transformation, language toolchains, and AI-assisted engineering workflows. The Staff Software Engineer in Test will establish scalable quality strategies, build automated validation and regression infrastructure, strengthen release evidence, diagnose complex systems failures, and lead quality practices across engineering teams.

Responsibilities:

• Assess existing validation practices, identify material gaps, and establish scalable quality strategies for code-generation, transpilation, and software-transformation workflows
• Strengthen quality practices for AI-assisted and agentic workflows, with sound judgment about reliability, reproducibility, risk, and appropriate oversight
• Build automated quality and regression infrastructure for AI-assisted software workflows that produces reproducible engineering evidence
• Strengthen and standardize quality signals and release evidence, including regression trends, failure attribution, validation results, and documented readiness criteria
• Diagnose complex failures across C/C++, Rust, Python, build systems, generated code, and heterogeneous target environments; make focused corrections where practical and partner with owning teams on deeper fixes
• Integrate validation suites and quality gates into delivery workflows while collaborating with, rather than replacing, the team responsible for shared CI/CD and developer infrastructure
• Lead quality practices for this space, establish technical standards, mentor engineers, and help shape the Quality Engineering function’s roadmap, operating model, and cross-team interfaces

Requirements:

• Significant experience in systems software, compiler or language tooling, developer tools, embedded software, or low-level execution environments
• Production-grade programming proficiency in Python and C++, plus the ability to read and debug unfamiliar C and Rust code
• Experience designing and scaling automated test frameworks, distributed execution systems, or evaluation pipelines for complex systems software
• Strong understanding of memory models, concurrency, runtime performance, and architecture-dependent behavior across CPU, GPU, embedded, or other constrained targets
• Hands-on experience with Linux, containerized environments, continuous integration platforms, and modern build systems
• Ability to translate ambiguous quality risks into measurable validation plans, explain tradeoffs clearly, and lead technical work across team boundaries
• Strong cross-functional collaboration skills, including partnering with Product to align validation strategies with the product value proposition and customer expectations
• Experience validating AI-assisted or nondeterministic software systems, with sound judgment about AI limitations, reproducibility, independent test evidence, and when deterministic controls or human oversight are required
• Typically 8+ years of relevant software engineering, test infrastructure, or quality engineering experience, with demonstrated Staff-level scope and impact. Equivalent depth of experience is valued over a rigid year count
• US Citizenship may be required for certain project assignments involving security clearance
• Experience improving and scaling quality practices for complex, nondeterministic, or high-consequence software systems
• Experience evaluating agentic or AI-assisted systems and translating their risks into practical quality controls
• Deep hands-on experience with compilers, language tooling, intermediate representations, ABI compatibility, or cross-language semantic validation
• Experience establishing repeatable validation environments and traceable engineering evidence
• Familiarity with formal verification and experience translating research methods into practical engineering checks
• Professional experience in regulated, safety-critical, or high-assurance domains such as defense, aerospace, automotive, medical devices, industrial systems, or semiconductor platforms