Job description

Job Description Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Austin TX IT Innovation Center or Warren Michigan 3 days per week (T-W-Th) Who We Are We are an engineering-focused IT organization responsible for the platforms, tools, and data ecosystems that power GM’s virtual engineering and simulation (CAE) capabilities. Our teams design , build, and operate high-performance computing, data, and AI/ML integration solutions that enable engineers to explore more design options, accelerate development cycles, and improve product quality. We partner closely with CAE, software, data science, and infrastructure teams to turn cutting-edge technologies into robust, production-ready capabilities that make GM’s vehicles safer, more efficient, and more innovative. The Role We are seeking a Senior Systems Engineer to lead the implementation, integration, and operationalization of AI/Machine Learning (AIML) solutions for the CAE engineering community. In this role, you will implement AIML based POC s as well as turn those POC s into robust, supportable capabilities by installing, configuring, and integrating commercial and custom AIML tools with GM’s CAE applications, HPC environments, and data platforms. You will partner closely with CAE engineers, other systems engineers, and infrastructure teams to ensure these solutions are reliable, performant, and straightforward for engineering users to adopt at scale. What You’ll Do Lead the installation, configuration, and integration of AIML software and services into existing and new CAE workflows, including on-prem and cloud/HPC environments. Integrate CAE tools, data sources, and AIML components (e.g., APIs, agents, pipelines, UIs) with enterprise platforms such as HPC clusters, Azure, data lakes, and Simulation Process and Data Management solutions. Define and maintain system-level requirements, interfaces, and architecture diagrams for AIML-enabled CAE solutions, ensuring traceability and alignment with enterprise standards. Develop and execute installation, integration, and regression test plans to validate end-to-end CAE workflows, including performance, reliability, and security checks. Partner with CAE engineers and business stakeholders to harden and scale successful AIML POCs, including packaging, deployment, monitoring, and support hand-off. Establish and improve operational processes (versioning, configuration management, logging, observability, incident response) for AIML-enabled CAE applications. Ensure all solutions comply with GM security, data governance, and responsible AI guidelines, including appropriate handling of engineering and proprietary data. Create and maintain user guides, runbooks, and integration documentation to support CAE engineers, support teams, and partner IT organizations. Provide technical leadership and mentorship to peers and junior engineers on CAE integration patterns, AIML solution deployment, and systems engineering best practices. Stay current on emerging AIML and CAE software capabilities and recommend pragmatic opportunities to simplify workflows, improve throughput, and reduce cycle time for engineering teams. Your Skills & Abilities (Required Qualifications) Bachelor’s degree in Systems Engineering, Software Engineering, Computer Science, Mechanical/Automotive Engineering, or a related technical field. 7 years of experience in systems engineering and/or software integration roles, with a focus on complex, distributed or HPC-based systems. Hands-on experience installing, configuring, and integrating engineering or scientific software (e.g., CAE solvers, pre/post tools, optimization/MBSE/AI tools) across desktop, HPC, and/or cloud environments. Strong background in systems engineering practices (requirements, interfaces, architecture, validation, and lifecycle management). Practical understanding of AI/ML concepts and patterns (e.g., model endpoints, inference services, pipelines, RAG/agentic workflows) and how they integrate into applications and workflows. Proficiency with scripting and automation (e.g., Python, shell, CI/CD tools) for installation, configuration, and validation of integrated systems. Experience working with HPC or cloud-based compute environments (e.g., job schedulers, containers, GPU resources, monitoring and logging tools). Demonstrated ability to collaborate with cross-functional teams (CAE engineers, software developers, data scientists, infrastructure, cybersecurity) to deliver integrated solutions. Excellent communication, documentation, and stakeholder-management skills; able to explain complex technical topics to diverse audiences. What Will Give You a Competitive Edge (Preferred Qualifications)    Master’s degree in Engineering, Systems Engineering, Computer Science, or a related field. Direct experience with CAE tools and workflows (e.g., structural, CFD, optimization, SPDM/EPDM) and how engineering teams run simulations in practice. Experience integrating or deploying commercial AIML/physics-AI tools within engineering environments. Familiarity with GM-like enterprise environments (regulated, safety-critical, or automotive) and associated security and compliance expectations. #LI-CK1 Gm does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need gm immigration sponsorship (e.g., H-1B, TN, STEM, OPT, etc.) Now or in the future. This job may be eligible for relocation benefits. About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Benefits Overview From day one, we re looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources . Non-Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire . Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

Requirements

Must-haves

Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Austin TX IT Innovation Center or Warren Michigan 3 days per week (T-W-Th)
What You’ll Do
Lead the installation, configuration, and integration of AIML software and services into existing and new CAE workflows, including on-prem and cloud/HPC environments.
Integrate CAE tools, data sources, and AIML components (e.g., APIs, agents, pipelines, UIs) with enterprise platforms such as HPC clusters, Azure, data lakes, and Simulation Process and Data Management solutions.
Define and maintain system-level requirements, interfaces, and architecture diagrams for AIML-enabled CAE solutions, ensuring traceability and alignment with enterprise standards.
Develop and execute installation, integration, and regression test plans to validate end-to-end CAE workflows, including performance, reliability, and security checks.
Partner with CAE engineers and business stakeholders to harden and scale successful AIML POCs, including packaging, deployment, monitoring, and support hand-off.
Establish and improve operational processes (versioning, configuration management, logging, observability, incident response) for AIML-enabled CAE applications.
Ensure all solutions comply with GM security, data governance, and responsible AI guidelines, including appropriate handling of engineering and proprietary data.
Create and maintain user guides, runbooks, and integration documentation to support CAE engineers, support teams, and partner IT organizations.
Provide technical leadership and mentorship to peers and junior engineers on CAE integration patterns, AIML solution deployment, and systems engineering best practices.
Stay current on emerging AIML and CAE software capabilities and recommend pragmatic opportunities to simplify workflows, improve throughput, and reduce cycle time for engineering teams.
Your Skills & Abilities (Required Qualifications)
Bachelor’s degree in Systems Engineering, Software Engineering, Computer Science, Mechanical/Automotive Engineering, or a related technical field.
7 years of experience in systems engineering and/or software integration roles, with a focus on complex, distributed or HPC-based systems.
Hands-on experience installing, configuring, and integrating engineering or scientific software (e.g., CAE solvers, pre/post tools, optimization/MBSE/AI tools) across desktop, HPC, and/or cloud environments.
Strong background in systems engineering practices (requirements, interfaces, architecture, validation, and lifecycle management).
Practical understanding of AI/ML concepts and patterns (e.g., model endpoints, inference services, pipelines, RAG/agentic workflows) and how they integrate into applications and workflows.
Proficiency with scripting and automation (e.g., Python, shell, CI/CD tools) for installation, configuration, and validation of integrated systems.
Experience working with HPC or cloud-based compute environments (e.g., job schedulers, containers, GPU resources, monitoring and logging tools).
Demonstrated ability to collaborate with cross-functional teams (CAE engineers, software developers, data scientists, infrastructure, cybersecurity) to deliver integrated solutions.
Excellent communication, documentation, and stakeholder-management skills; able to explain complex technical topics to diverse audiences.
Master’s degree in Engineering, Systems Engineering, Computer Science, or a related field.

Nice-to-haves

What Will Give You a Competitive Edge (Preferred Qualifications)

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Keywords to mirror

aimlmachine learningazurepythonci/cd

Platform: workday
Effort: long

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