Senior AI-Driven Cloud Security Engineer

General Motors Company; Michigan; Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Hybrid work model

Relocation benefits available

Total Rewards resources

Job summary

General Motors’ Advanced Security Engineering team develops security capabilities to reduce real exposure. You will design, build, and operate cloud services and AI agents supporting this work, handling untrusted code and sensitive data in controlled environments.

You will work independently, own delivery across teams, and mentor engineers while balancing reliability, security, and cost considerations as part of a hybrid role at GM.

Qualifications

• Bachelor’s degree in Computer Science, Cybersecurity, Engineering, or a related field, or equivalent practical experience.
• 5+ years of experience in software engineering, cloud engineering, or security engineering.
• Strong experience writing production Python.
• Experience with infrastructure as code, such as Terraform, and CI/CD on a major cloud platform.
• Working knowledge of application security, including common vulnerability classes, how security scanners work, and where they produce false positives.
• Experience building secure systems using least privilege, secrets management, isolation, and safe handling of untrusted input.
• Ability to own work across teams, make sound decisions with limited information, and explain technical risk to people who are not security specialists.
• Experience using agentic large language model (LLM) tools and solutions.

Responsibilities

• Design, build, and operate production cloud services in Python, including containerized workloads, event-driven processing, and data storage.
• Define and manage the supporting infrastructure as code.
• Integrate findings and context from security tools, source control, and cloud application programming interfaces (APIs).
• Build AI agents that triage findings, gather evidence from source code and cloud configuration, and propose fixes.
• Build and harden sandboxed environments for AI-enabled testing of authorized targets.
• Apply defense in depth, designing for the possibility that any individual containment boundary can fail. Control agent access through isolation, least-privilege identities, network egress limits, and secrets management. Separate agents that produce results from those that verify them.
• Treat source code, tool output, and model responses as untrusted input, defend against prompt injection, and keep sensitive data out of prompts and logs.
• Evaluate model accuracy, cost, and latency to inform model selection and detect regressions. Use evidence to explain technical trade-offs and guide improvements to the systems you own.
• Partner with application security, penetration testing, and cloud security engineers to turn expert judgment into repeatable checks and deliver solutions across teams.
• Communicate technical risks and recommendations to non-specialists, review code, and mentor less-experienced engineers through constructive feedback and collaborative problem-solving.

Skills

Python development

Cloud engineering

Security engineering

CI/CD

Terraform

Application security

Least privilege

LLM tools

Education

Bachelor’s degree in Computer Science, Cybersecurity, Engineering, or related field

Tools

Kubernetes

Job description

General Motors’ Advanced Security Engineering team develops security capabilities to reduce real exposure. You will design, build, and operate cloud services and AI agents supporting this work, handling untrusted code and sensitive data in controlled environments.

You will work independently, own delivery across teams, and mentor engineers while balancing reliability, security, and cost considerations as part of a hybrid role at GM.