Senior SaaS & AI Cyber Security Engineer
General Motors1 day ago
Warren, MI, USASenior
Responsibilities
- Develop and mature the SaaS security program through application inventory, security baselines, configuration standards, and continuous control monitoring.
- Assess SaaS platforms and integrations for identity, access, data protection, logging, privacy, resilience, and third-party risk.
- Strengthen SSO, MFA, privileged access, service accounts, OAuth applications, and lifecycle controls with application owners.
- Identify and reduce risks involving misconfiguration, excessive permissions, unmanaged integrations, shadow SaaS, data exposure, and insecure administration.
- Support security architecture reviews, control design, exception management, and remediation tracking for SaaS solutions.
- Automate security assessments, monitoring, evidence collection, and remediation workflows, including development of custom AI agents.
- Develop and implement controls governing sanctioned AI tools, users, data, integrations, access paths, monitoring, and policy enforcement.
- Maintain visibility into AI use cases, models, providers, data flows, agents, tools, plugins, and business owners.
- Develop repeatable security review patterns for AI products and translate emerging threats into controls, detections, and engineering guidance.
- Partner with legal, privacy, compliance, procurement, data governance, product, engineering, and business teams to support secure AI adoption.
- Create standards, playbooks, reference architectures, training, security awareness materials, and executive-ready risk summaries.
- Mentor and guide junior security engineers.
Requirements
- Bachelor's or master's degree in Computer Science, Cybersecurity, Engineering, or a related field.
- Minimum of 7 years of cybersecurity experience with significant focus on SaaS security and AI-driven security solutions.
- Strong understanding of cybersecurity principles, protocols, and best practices.
- Demonstrated experience with identity federation, access governance, API and OAuth security, configuration assessment, logging, and data protection.
- Working knowledge of AI/ML security risks and experience assessing AI-enabled applications, workflows, or third-party services.
- Experience with security architecture reviews, risk assessment, or security control validation.
- Experience designing, building, and securing AI agents.
- Ability to write clear technical requirements, security standards, findings, and executive-ready risk summaries.
- Excellent communication, analytical, and problem-solving skills, with the ability to work independently and collaboratively.
- CISSP or equivalent certification is highly desirable.
- Familiarity with NIST AI Risk Management Framework, OWASP Top 10 for LLM Applications, MITRE ATLAS, or comparable practices is preferred.
- Experience with security data analysis, data engineering, dashboards, or analytics is preferred.
Benefits
- Hybrid work arrangement requiring reporting to Warren, MI three times per week.
- Relocation is not available for this role.
- GM provides benefits supporting employee well-being at work and at home from day one.
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About General Motors
General Motors designs, manufactures, and sells cars, trucks, and electric vehicles for consumers and commercial fleets under brands including Chevrolet, GMC, Cadillac, and Buick. A public company on the NYSE headquartered in Detroit and founded in 1908, it operates globally and is developing EVs on its Ultium battery platform. Revenue comes from vehicle and parts sales, connected services such as OnStar, and financing through GM Financial.