Senior Systems Engineer – CAE AIML Integration & Implementation

General Motors Africa & Middle East; Warren (MI); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Relocation benefits

Hybrid work model

Job summary

General Motors seeks a Senior Systems Engineer to lead AIML integration for CAE engineering, deploying POC efforts into scalable, supported capabilities across on-prem and cloud/HPC environments.

You will collaborate with CAE engineers, software developers, data scientists, and infrastructure teams to ensure reliable, performant solutions while adhering to security and governance standards. Strong communication and documentation are essential.

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 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 and how they integrate into applications and workflows.
• Proficiency with scripting and automation (e.g., Python, shell, CI/CD tools).
• 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).
• Excellent communication, documentation, and stakeholder-management skills; able to explain complex technical topics to diverse audiences.

Responsibilities

• Lead installation, configuration, and integration of AIML software into CAE workflows across on-prem and cloud/HPC environments.
• Integrate CAE tools, data sources, and AIML components with enterprise platforms like HPC clusters, Azure, data lakes, and SPDM/EPDM-style systems.
• Define system-level requirements and architecture diagrams for AIML-enabled CAE solutions with traceability to enterprise standards.
• Develop and execute installation, integration, and regression test plans for end-to-end CAE workflows; ensure performance, reliability, and security.
• Harden and scale AIML POCs; package, deploy, monitor, and hand off to support.
• Establish and improve operational processes (versioning, configuration management, logging, observability, incident response).
• Ensure solutions comply with GM security, data governance, and responsible AI guidelines.
• Create and maintain user guides, runbooks, and integration documentation for CAE engineers and partner IT.
• Provide technical leadership and mentorship on CAE integration patterns and AIML deployment.
• Stay current on AIML/CAE capabilities and identify opportunities to simplify workflows and improve throughput.

Skills

AIML integration

HPC/Cloud environments

Python scripting

Systems engineering

Stakeholder communication

Documentation

Education

Bachelor's degree in Systems/Software/CS/Engineering

Master's degree (preferred)

Tools

CAE tools

Azure

CI/CD tools

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.

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.

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