Senior Systems Engineer – CAE AIML Integration & Implementation

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 GMs 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 GMs 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 this role you will implement AIML based POCs as well as turn those POCs into robust supportable capabilities by installing configuring and integrating commercial and custom AIML tools with GMs 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 Youll 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)

• Bachelors 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)

• Masters 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

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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.

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