AI Enablement & Governance Lead – Policy, Controls & Compliance

Alight

9h•Remote

About The Position

The AI Enablement & Governance Lead – Policy, Controls & Compliance is responsible for enabling responsible and scalable AI adoption by defining clear AI governance policies, standards, and control requirements across the AI lifecycle. This role acts as the functional owner for AI governance policy and controls definition, translating regulatory expectations and industry frameworks into practical, enforceable requirements and documented control expectations. The Lead will collaborate closely with AI Engineering, Legal, Privacy, Security, and Audit teams to ensure governance and compliance requirements are embedded by design, making sure AI solutions are auditable, sustainable, and aligned with enterprise risk and trust expectations.

Requirements

5–8+ years of experience in AI governance, model risk management, compliance, audit, privacy, or related risk functions.
Industry certifications such as Certified AI Governance Professional (AIGP), Advanced in AI Audit (AAIA), Risk & AI Certificate (RAI), or similar credentials.
Demonstrated ability to translate technical AI concepts into policies, standards, and control requirements.
Practical, risk‑based mindset with the ability to balance compliance rigor with business adoption.
Strong written communication skills, judgment, and attention to detail.

Responsibilities

Owning, developing, and maintaining enterprise AI governance policies and standards, including Responsible AI principles, acceptable use, documentation requirements, and defined risk thresholds.
Establishing and maintaining the AI policy hierarchy, ensuring clear alignment between enterprise policy, supporting standards, and control requirements.
Translating external regulatory expectations and industry frameworks (e.g., NIST AI Risk Management Framework) into clear, enforceable enterprise policies and standards.
Ensuring AI governance policies and standards remain current with evolving regulations, supervisory guidance, technology capabilities, and business use cases.
Defining policy exception criteria and escalation pathways; exception approval is governed through established enterprise processes.
Identifying, define, and document AI governance controls that enable compliance with policy, regulatory, and risk management obligations.
Developing clear control statements that articulate control intent, scope, applicability, and expected evidence artifacts across the AI lifecycle.
Defining minimum control requirements based on AI risk tier, model characteristics, data sensitivity, and usage context.
Partnering with engineering, security, and delivery teams to ensure AI controls are implementable, measurable, and embedded into SDLC and operational workflows.
Maintaining authoritative documentation of AI controls to support audit, regulatory review, and internal assurance activities.
Supporting client‑facing teams by providing standardized, defensible AI governance policy and control content for inquiries, RFPs, and due diligence requests.
Assisting in preparing clear, business friendly explanations of AI governance practices for clients and auditors.
Providing guidance to ensure AI usage aligns with contractual, regulatory, and trust expectations.
Providing guidance on policy and control alignment to ensure AI usage meets contractual, regulatory, and trust expectations.
Supporting AI risk classification, documentation traceability, and audit readiness across AI use cases, models, tools, and vendors.
Assisting with preparation and maintenance of AI governance evidence for audits, regulatory reviews, and client inquiries (e.g., SOC 2, ISO, due diligence).
Tracking AI‑related findings and remediation status to inform continuous improvement of governance policies, standards, and controls.