Cyber Security Consultant

AI Governance Lead (Cyber Security Consultant III)

Position Overview

We are seeking an experienced AI Governance Lead to operationalize and manage enterprise-wide AI and GenAI governance. This role sits at the intersection of cybersecurity, risk, data governance, and compliance, and is responsible for turning governance frameworks into actionable, scalable processes.

This is not a hands-on engineering role. Instead, the focus is on program execution, cross-functional leadership, and audit readiness, ensuring AI solutions are deployed responsibly and in alignment with regulatory, security, and ethical standards.

You will act as a central liaison across business, legal, compliance, audit, and technical teams, driving clarity, consistency, and execution across all AI initiatives.

Key Responsibilities

AI Governance & Strategy

• Define and apply governance prioritization criteria for AI/GenAI use cases (value, risk, feasibility, compliance)

• Develop, own, and continuously improve AI/GenAI policies, standards, and guidelines

• Establish governance frameworks covering acceptable use, model development, testing, release, and human oversight

Operationalization & Execution

• Operationalize AI governance “end-to-end” (intake → design → build → validate → deploy → monitor → retire)

• Define and enforce control checkpoints across the AI lifecycle

• Build and maintain a centralized governance library (templates, SOPs, model cards, playbooks, risk assessments)

• Ensure teams follow established governance processes and standards

Risk, Compliance & Audit

• Lead AI risk identification, assessment, and mitigation across domains:

  • Privacy & data protection

  • Cybersecurity

  • Bias & fairness

  • Explainability

  • IP/copyright

  • Model misuse & safety

• Partner with enterprise risk, legal, compliance, privacy, and security teams

• Coordinate audit readiness (including SOX controls where applicable), ensuring traceability and evidence retention

• Work directly with audit teams to close findings and operationalize controls

Model Governance & Validation

• Establish and oversee model validation practices (performance, drift, bias, robustness, stress testing, red teaming)

• Maintain complete and accurate model inventory (ownership, usage, data sources, risk tiering)

• Define classification frameworks for AI models and associated data

Data & Vendor Alignment

• Partner with Data Governance teams on data quality, lineage, access, classification, and retention

• Collaborate with SVRA / third-party risk teams to ensure vendor compliance with enterprise standards

• Stay informed on vendor/tool capabilities and communicate implications to stakeholders

GenAI Guardrails

• Define and monitor guardrails including:

  • Prompt injection protections

  • Data leakage controls

  • Content filtering

  • Safe output handling

Program Leadership & Stakeholder Management

• Act as the central point of coordination across all AI governance activities

• Manage cross-functional workflows and ensure alignment across teams

• Maintain and update Jira boards, track deliverables, and communicate progress

• Funnel and triage stakeholder questions, reducing dependency on leadership

• Lead meetings with internal teams, audit partners, and external advisors (e.g., consulting partners)

What You’ll Do in Your First Weeks

• Partner with AI enablement teams and consulting partners to align on governance strategy

• Engage audit and compliance stakeholders to assess current gaps

• Begin operationalizing governance controls and closing audit findings

• Stand up tracking mechanisms and governance workflows

• Establish initial standards and communication channels across teams

Required Qualifications

• 7–9 years of experience in AI governance, risk, cybersecurity, data governance, or related fields

• Strong understanding of AI/GenAI technologies and associated risks

• Experience operationalizing governance frameworks or compliance programs

• Proven ability to work across matrixed organizations and multiple stakeholders

• Experience supporting audit, regulatory, or SOX control environments

• Strong program/project management skills (e.g., Jira, Agile workflows)

• Excellent communication skills with ability to translate technical concepts into business terms

• Ability to work independently and drive execution with minimal oversight

Preferred Qualifications

• Experience in regulated industries (e.g., energy, utilities, finance)

• Familiarity with AI governance frameworks (e.g., NIST AI RMF, model risk management)

• Experience working with consulting firms (e.g., BCG) or enterprise transformation initiatives

• Background in data management, analytics, or machine learning lifecycle processes

Key Skills

• AI/GenAI Governance & Risk Management

• Program & Project Leadership

• Cross-Functional Stakeholder Management

• Data & Model Lifecycle Understanding

• Audit & Compliance Execution

Additional Details

• Team Structure: Individual contributor working closely with leadership; high visibility role

• Work Environment: Highly cross-functional, fast-moving, and evolving AI landscape

• Conversion Potential: High likelihood of extension or full-time conversion