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Senior AI Security Engineer
Credit AcceptanceAI Security Engineer at Credit Acceptance securing AI and ML systems with a focus on compliance and risk mitigation. Collaborate globally to embed security into AI systems by design.
Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud Platform
About the role
Key responsibilities & impact- Partner with engineering and data science teams to design and review AI architectures, including agentic and multi‑agent systems, for security, privacy, and regulatory compliance.
- Perform security reviews of AI/ML systems, including model lifecycle, data pipelines, inference APIs, agent orchestration layers, and third‑party AI services.
- Identify and mitigate risks such as: Data leakage and model exploitation, Prompt injection and indirect prompt manipulation, Agent autonomy risks (over‑permissioned agents, unsafe tool use, uncontrolled action execution), Insecure model deployment and inference exposure.
- Support threat modeling and risk assessments for AI and agent‑driven workflows, assisting teams in implementing practical mitigations.
- Contribute to and operationalize AI and agentic AI security standards, guidelines, and secure design patterns used across the company.
- Evaluate AI platforms, agent frameworks, and vendors to ensure alignment with security, privacy, and compliance requirements.
- Support responsible AI practices related to explainability, oversight, auditability, and controlled autonomy, in collaboration with legal, compliance, and risk partners.
- Act as a trusted security advisor to teams adopting AI, LLM‑based agents, and workflow‑oriented AI systems.
- Participate in design reviews and working sessions focused on secure AI and agent deployment.
- Provide guidance on secure use of generative AI, internal AI platforms, and agent‑based tools interacting with company systems and data.
- Stay current on AI and agentic AI security threats, vulnerabilities, and best practices.
- Recommend improvements to tooling, processes, and controls to strengthen AI security posture.
- Contribute to internal documentation, training materials, and security enablement related to AI and agent usage.
Requirements
What you’ll need- Bachelor’s Degree or equivalent experience
- 5+ years of experience in application security, cloud security, or product security.
- 2 + years of experience in AI security
- Experience securing AI/ML systems, LLM‑based agents, or generative AI platforms.
- Familiarity with risks unique to agentic AI, such as excessive autonomy, privilege escalation through tools, and unsafe action execution.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerized environments.
- Knowledge of regulatory and governance considerations related to AI and automated decision systems.
- Experience embedding security into software development workflows (DevSecOps).
Benefits
Comp & perks- Flexible work options including work from home, on site and hybrid positions
- Company provided technology packages for all Team Members
- An atmosphere that is collaborative, challenging, and filled with forward thinking Team Members
- Extensive growth opportunities as demonstrated by our track record of promoting internally
- Ongoing business training and career development opportunities
- Competitive market-based salary with bonus compensation, quarterly profit sharing and annual merit bonuses
- Generous PTO and holidays that include 27.5 total days during first full year of employment
- Excellent benefits package that includes 401(K) match, adoption assistance, parental leave, tuition reimbursement, comprehensive medical/ dental/vision and many nonstandard benefits that make us a Great Place to Work
ATS Keywords
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Hard Skills & Tools
AI securityapplication securitycloud securityproduct securitysecuring AI/ML systemsgenerative AI platformsDevSecOpsrisk assessmentthreat modelingdata pipeline security
Soft Skills
collaborationcommunicationadvisory skillsproblem-solvingguidancetrainingdocumentation
Certifications
Bachelor’s Degree