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Job Description
At Cetera, our Information Security organization protects employees, advisors, and clients from evolving cyber threats across cloud, SaaS, and emerging AI-enabled technologies. As artificial intelligence capabilities expand across the enterprise, Cetera is building a formal AI risk and compliance program - grounded in industry-recognized AI risk management frameworks - to ensure innovation aligns with regulatory, security, and third-party risk expectations.
We are seeking an AI Risk and Compliance Engineer to operationalize AI governance controls, manage AI-related third-party and vendor risk, and lead adversarial threat modeling for AI/ML systems using the MITRE ATLAS framework. This role serves as a key bridge across IT Risk, Cloud Security, Legal/Procurement, and AI/ML Engineering teams, translating AI risk management framework requirements into practical, auditable processes within a regulated financial services environment.
What will you do:
Operationalize AI governance controls: Implement and maintain controls aligned to recognized AI risk management frameworks (spanning governance, mapping, measurement, and management of AI risk), including control documentation, risk-control matrices (RCM), and evidence collection to support audits and regulatory exams.
Lead AI third-party risk management: Evaluate and onboard third-party AI/ML tools and vendors against security, privacy, and compliance criteria; document AI-specific vendor and contract requirements, SLAs, and fourth-party disclosures; support due diligence for AI vendors and data provenance reviews.
Maintain AI/vendor risk inventories: Build and maintain documentation of third-party AI components (models, datasets, APIs, pre-trained/foundation models) covering provenance, functionality, and known limitations, and map internal controls to those components.
Run ongoing AI risk assessments: Conduct recurring vendor risk and compliance assessments covering AI system performance, data quality, algorithmic bias, and security controls; monitor pre-trained/foundation model drift and SLA adherence; assess concentration and dependency risk across AI vendors.
Perform AI threat modeling: Design and execute threat models for AI/ML systems using the MITRE ATLAS framework to identify adversarial tactics and techniques - including prompt injection, data/model poisoning, model evasion, model extraction, and supply-chain risk in ML pipelines - across the AI development and deployment lifecycle.
Coordinate adversarial testing: Plan and coordinate red-teaming, adversarial testing, and penetration testing of AI/ML systems, and drive ongoing threat assessments informed by current threat intelligence and prior incidents.
Integrate AI into vulnerability management: Ensure AI-specific vulnerabilities and security findings are captured, prioritized, and remediated through existing enterprise vulnerability management processes.
Identify and assess unsanctioned AI usage: Support discovery and risk assessment of unsanctioned (shadow) AI tool usage across the enterprise and recommend remediation or approval pathways.
Partner cross-functionally: Work closely with IT Risk, Cloud Security, Legal, Procurement, and Application/AI Engineering teams to embed AI risk and compliance requirements into intake, procurement, and development processes.
Support governance and audit activities: Develop and maintain AI risk standards, control narratives, and runbooks; support internal and external audits and regulatory compliance activities (e.g., FINRA) by producing control evidence tied to the organization's AI risk management framework.
What you will have:
8-10+ years of experience in IT/cyber risk, GRC, security engineering, or a related discipline, with direct exposure to AI/ML systems
Working knowledge of AI risk and control frameworks (e.g., NIST AI RMF or similar industry AI risk management frameworks) and OWASP Top 10 for LLMs
Practical experience with, or strong working knowledge of, threat modeling methodologies for AI/ML systems, including familiarity with MITRE ATT&CK and MITRE ATLAS
Experience building or operating third-party/vendor risk management processes - due diligence, contracting/SLAs, ongoing monitoring, and issue remediation
Understanding of AI-specific attack techniques (prompt injection, data/model poisoning, model evasion, model extraction/inversion) and associated mitigations
Ability to translate technical risk findings into control objectives, policy language, and audit-ready documentation
Experience in regulated environments (financial services or FINRA preferred)
Strong communication skills across technical, risk, legal, and compliance stakeholders
Preferred Qualifications:
Experience with GRC platforms (e.g., Archer, ServiceNow GRC) for control and risk-register management
Certifications such as CRISC, CISSP, CCSP, or IAPP AIGP (AI Governance Professional)
Experience with AWS Bedrock or other cloud AI/ML platforms and cloud-native AI security
Familiarity with model cards, data lineage/provenance tooling, and AI bill-of-materials (AI-BOM) concepts
Prior participation in red team, purple team, or adversarial testing exercises involving ML systems
Exposure to AI governance committees or model risk management (MRM) functions