Descripción

We are seeking a highly skilled Staff Software Engineer to join the Virtualization & Embedded Software Development Tools organization.

In this role, you will apply artificial intelligence to improve developer productivity, modernize engineering workflows, and advance toolchain capabilities across embedded software development. You will shape and deliver practical, production-grade AI capabilities that help engineers build, test, analyze, troubleshoot, and support complex software systems more effectively at scale.

This role is ideal for a recognized technical expert who thrives in ambiguity, works independently with broad latitude, influences key technical decisions, and leads large cross-functional efforts with broad visibility. You will partner across CI/CD, virtualization, systems engineering, calibration, platform, and software development teams to identify high-value opportunities and turn them into scalable solutions that improve engineering throughput, reliability, and user experience.

Our organization supports the end-to-end engineering toolchain that enables teams to define, develop, validate, calibrate, and release embedded software and systems. That includes engineering tools, build and test workflows, dashboards, automation, integrations, and engineering support platforms. As part of this team, you will help define how AI can be used responsibly and effectively in real engineering environments to improve speed, quality, and user experience.

What you’ll do

Define the technical vision for AI-powered developer productivity capabilities across engineering tools and workflows
Design, develop, and deliver AI-powered solutions that reduce manual effort, accelerate issue resolution, and improve software quality across development, debugging, test analysis, issue triage, documentation, and engineering support workflows
Partner with cross-functional teams to identify high-value AI use cases and translate them into scalable products, platforms, and reusable capabilities
Integrate AI-powered capabilities into engineering tools, workflows, and automation platforms in ways that improve reliability, usability, and adoption
Lead architecture and implementation decisions for AI systems spanning model access, orchestration, retrieval, evaluation, observability, security, and enterprise integration
Drive productionization of AI capabilities within GM engineering environments, including cloud-hosted services, internal platforms, CI/CD systems, and developer tools
Establish technical standards and best practices for responsible use of AI in engineering tools, including quality, traceability, maintainability, and cybersecurity considerations
Serve as a subject matter expert and technical leader across organizational boundaries, influencing roadmaps, solution direction, and implementation priorities
Mentor engineers on AI system design, prompt and workflow design, evaluation strategies, and toolchain integration without formal people-leader responsibility
Present strategy, progress, recommendations, and demonstrations to technical leaders and partner organizations

Additional job description

Your skills and abilities (required qualifications)

Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering, or a related technical field
10+ years of experience in software engineering, developer tooling, platform engineering, machine learning engineering, applied AI, or a closely related field
Strong expertise building and shipping production software systems, with proficiency in Python and at least one additional language used in engineering tooling environments
Demonstrated expertise applying AI and LLM-based approaches to engineering problems such as code analysis, workflow automation, knowledge retrieval, summarization, troubleshooting, or developer productivity support
Strong understanding of software engineering fundamentals, system design, APIs, data flows, observability, and production operations
Experience integrating AI-powered capabilities into enterprise platforms, engineering tools, or CI/CD systems
Experience with cloud services, containerization, and orchestration technologies
Strong knowledge of secure engineering practices and responsible AI guardrails
Demonstrated success leading technically ambiguous, cross-functional efforts from concept through production deployment
Excellent communication skills and the ability to influence technical direction across teams without formal authority
Experience with developer platforms, build systems, testing systems, or internal engineering tools
Experience balancing fast experimentation with production reliability, maintainability, and compliance

What can give you a competitive edge (preferred qualifications)

Master’s degree or PhD in Computer Science, Software Engineering, Machine Learning, AI, or a related field
Experience in embedded software development, automotive software, systems engineering, or safety-related toolchains
Experience with CI/CD platforms, build and test orchestration, and software quality automation
Familiarity with GM engineering tools, engineering workflows, or internal platform environments
Experience building AI assistants, coding agents, or domain-specific AI capabilities for engineers
Experience with knowledge systems, vector search, ranking, workflow orchestration, or code intelligence platforms
Experience supporting large engineering communities through reusable tools, templates, and automation
Experience evaluating AI quality in production systems using measurable outcomes such as acceptance rate, time saved, precision and recall, hallucination reduction, or workflow completion rate
Experience designing retrieval-augmented or tool-using AI workflows
Experience integrating AI into GitHub-based engineering workflows or related enterprise automation pipelines

Why join us

This is an opportunity to shape how AI is applied in real-world engineering environments at scale. You will work on high-value problems at the intersection of developer productivity, toolchain modernization, automation, CI/CD, observability, and embedded software development. Your work will help engineering teams move faster, reduce friction, improve quality, and unlock new capabilities across a critical part of GM’s software development ecosystem.

You will join a team that is actively modernizing and scaling core engineering toolchains, including CI/CD robustness, workflow automation, dashboarding and observability, configuration and calibration workflows, and platform evolution. This role offers the opportunity to turn promising AI concepts into reliable, enterprise-ready capabilities that deliver measurable value.

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position, as well as geography of the selected candidate.
       • The salary range for this role is ($160,200 - 246,300). The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
       • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Benefits:
       • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

#LI-JK3

GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc.)

Este puesto se clasifica como híbrido. Esto significa que se espera que el candidato seleccionado se presente en una ubicación específica al menos 3 veces por semana {o con otra frecuencia indicada por su líder}.

Este puesto no es elegible para beneficios de reubicación. Los posibles costos de relocalización serán responsabilidad del candidato seleccionado.

Información sobre diversidad

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Adecuaciones (EE.UU. y Canadá)

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