Principal Software Engineer - Build System Modernization

Description

The company builds software-defined vehicles and is looking for a software engineering leader to modernize and scale the build systems behind them.

The role leads the move from a legacy Make-based system to Bazel, Google's open-source build tool, with the goal of faster, more reliable builds across the engineering organization.

The leader drives this work at scale, shapes technical direction across teams, and sets ambitious platform goals.

The work covers software engineering productivity: spotting opportunities, setting strategy, improving processes, guiding change, and linking initiatives so they simplify work and add value.

You will work hands-on on hard and unusual problems while coaching and mentoring others with both technical depth and empathy.

Responsibilities

• Assess the current Make-based build, test, dependency, toolchain, and hardware workflows, then define a phased Bazel migration plan and rollout approach.
• Modernize a large embedded build and test system by moving Make and shell workflows to Bazel, with scalable, reproducible, secure, and developer-friendly infrastructure across repositories, toolchains, CI/CD, testing, and releases.
• Build reusable Bazel rules, macros, toolchains, platforms, configuration patterns, and repository standards for embedded software.
• Migrate embedded applications, libraries, generated code, firmware, cross-compilation flows, and platform variants, confirming build parity and reproducibility at each step.
• Connect Bazel to enterprise CI/CD, testing, release, artifact, deployment, observability, security, and infrastructure systems.
• Improve performance and reliability through caching and parallelism, write documentation, run training, retire the legacy Make system, and keep improving the platform.
• Track results: completed migrations with verified build and test parity, shorter clean and incremental builds, CI queue times, and developer feedback times, higher reproducibility, hermetic toolchain adoption, cache hit rates, and CI capacity, and lower build, pipeline, and flaky-test rates.
• Shorten diagnosis and recovery times, and make sure releases have full artifact provenance, test evidence, and security policy compliance. Drive developer adoption, reduce support load, and show measurable productivity gains.
• Evaluate AI-enabled engineering workflows using measurable quality, adoption, and productivity results.

Requirements

• A bachelor's degree in software engineering or equivalent experience, plus 15 years or more of software development experience.
• Solid understanding of real-time software architecture.
• Experience shipping high-quality, safety-critical products.
• Strong problem-solving and analytical skills with close attention to detail.
• A track record of managing several projects and priorities in a fast-moving, action-oriented decision environment.
• Strong experience building and running production software, with Python and at least one other language used for engineering tooling.
• Experience in automotive, embedded, safety-related, calibration, or systems engineering settings.
• Experience migrating large build orchestration from Make or shell scripts to Bazel.
• Experience with AI-assisted developer productivity, coding agents, code intelligence, knowledge retrieval, or workflow orchestration.
• Experience evaluating AI-enabled engineering workflows with measurable quality, adoption, and productivity outcomes.
• Preferred: a master's degree or PhD in computer science, software engineering, machine learning, AI, or a related field.
• Preferred: experience in embedded, automotive, systems engineering, or safety-related toolchains.
• Preferred: familiarity with GM engineering tools, engineering workflows, or internal platform environments.
• Preferred: experience building AI assistants, coding agents, or domain-specific AI tools for engineers.
• Preferred: experience with knowledge systems, vector search, ranking, workflow orchestration, or code intelligence platforms.
• Preferred: experience supporting large engineering communities with reusable tools, templates, and automation.
• Preferred: experience measuring AI quality in production using outcomes such as acceptance rate, time saved, precision and recall, hallucination reduction, or workflow completion rate.

Conditions

The role is remote. If the selected candidate lives within a set mile radius of a GM hub, they must work from that location three times a week, or at another frequency the manager sets.

The base salary range is 201,000 to 400,000. The offer within that range depends on job-related factors and the candidate's location. The range is a good-faith estimate under applicable state law.

Pay includes an incentive program based on company performance, job level, and individual performance.

Eligibility for a company vehicle evaluation program requires a successful motor vehicle report review.

Some applicants may need to pass a role-related assessment or a pre-employment screening before starting.

The company is committed to equal employment opportunity and an inclusive workplace.

Benefits

• Health and wellbeing coverage, including medical, dental, vision, a Health Savings Account, and Flexible Spending Accounts.
• A retirement savings plan, sickness and accident benefits, and life insurance.
• Paid vacation and holidays, tuition assistance, and an employee assistance program.
• Discounts on company vehicles, plus other perks.
• Relocation support for candidates who qualify under company policy.
• Participation in the company vehicle evaluation program, where you are assigned a company vehicle to drive and evaluate. Participants must buy or lease a qualifying company vehicle every four years unless a limited exception applies.