AI Security Architecture and Risk, Sr Advisor

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We’re Fiserv, a global leader in Fintech and payments, and we move money and information in a way that moves the world. We connect financial institutions, corporations, merchants, and consumers to one another millions of times a day – quickly, reliably, and securely. Any time you swipe your credit card, pay through a mobile app, or withdraw money from the bank, we’re involved. If you want to make an impact on a global scale, come make a difference at Fiserv.

Job Title

AI Security Architecture and Risk, Sr Advisor

About your role

You will lead the security design and risk-assessment approach for the enterprise AI program at Fiserv, shaping the reference architectures, risk tiering, and guardrail standards that let the business adopt AI quickly and safely. Sitting within Cybersecurity, this role helps lead a cross-functional model for AI security that connects the strengths of Cyber, the AI Center of Excellence, Cybersecurity Architecture, Risk, and the business units. It is a cornerstone of the AI Security Protection team and a driver of the Fiserv transformation to secure-by-design AI delivery.

What you’ll do

• Help lead the enterprise AI security reference architecture — partnering with Cybersecurity Architecture and the AI Center of Excellence to define approved patterns and secure defaults for AI and agentic workloads, and to evaluate incoming designs against them.
• Help build and steward the AI risk-assessment framework — a multi-factor risk-tiering model that routes initiatives into delivery lanes (Standard, Elevated Risk, Experimentation) with clear, auditable criteria for rapid, consistent decisions at scale.
• Define the control requirements and thresholds that AI protection tooling enforces — guardrail thresholds for hallucination, PII/PHI exposure, prompt injection, and toxicity, plus data-access policy — and bring security leadership to the build-vs-buy strategy for that layer (e.g., Arize, Fiddler, Varonis, or equivalent).
• Develop and maintain STRIDE, MAESTRO, and MITRE ATLAS threat models for new AI system patterns, and contribute the Architecture Decision Records that keep the program defensible to internal auditors and regulators.
• Represent Cyber’s AI security perspective in AI Center of Excellence governance, and help translate design decisions into platform-enforceable policy and guardrails.
• Evaluate emerging agentic AI frameworks (multi-agent orchestration, LLM tool-calling, autonomous workflows) for architectural risk and help define secure defaults with partner teams before they reach production.
• Lay the groundwork for a future automation layer by designing controls and decision logic so they can be progressively operated by AI agents as the program matures.
• Responsibilities listed are not intended to be all-inclusive and may be modified as necessary.

Experience you’ll need to have

• 10+ years in security architecture, with a focus on cloud-native, AI/ML, or platform security domains.
• Hands-on proficiency with AI risk frameworks: NIST AI RMF, MITRE ATLAS, OWASP LLM Top 10, and ISO/IEC 42001, MAESTRO.
• Demonstrated experience designing risk-classification or governance models that balance security assurance against delivery speed.
• Experience with policy-as-code tooling (Sentinel) and translating security policy into platform-enforceable controls.
• Familiarity with the commercial AI protection landscape — observability, guardrails, and data security posture management — sufficient to make credible build-vs-buy and tooling recommendations.
• A track record of leading through influence across organizational boundaries, building alignment with governance, platform, and business teams to deliver shared outcomes.
• Strong technical communication skills; proven ability to present architecture and risk positions to SVP and C-suite audiences.
• Bachelor’s degree in Computer Science, Cybersecurity, or a related field, and/or equivalent work experience.

Experience that would be great to have

• Experience in financial services or other regulated industries with AI governance under frameworks such as the EU AI Act, ISO/IEC 42001, or model risk guidance such as SR 11-7.
• Hands-on experience evaluating LLM-based agent orchestration systems (LangGraph, AutoGen, CrewAI, or equivalent) in a security or governance context.
• Experience helping shape cross-functional operating models as organizations scale new …