Head of Responsible AI

Role:

As the Chief Responsible & Secure AI Officer, you will be the primary architect of trust for the enterprise. Reporting jointly to the Chief Information Officer (CIO) and the General Counsel (GC), you will mature and institutionalize the function that ensures all AI initiatives are ethically sound, legally compliant, and architecturally resilient.

In a data-centric operations environment, this role serves as the bridge between technical innovation and legal safeguard—enforcing a dual mandate: accelerating AI adoption while minimizing systemic risk.

Key Responsibilities:

1. Strategic Leadership & Governance

• Operationalize the Charter: Define the 3-year maturity roadmap for Responsible & Secure AI, aligning it with client commitments and global regulations.
• Together with the GC and CIO, lead the AI Governance Committee to ensure a single, unified voice on AI approval and deployment.
• The Enterprise Voice: Function as the lead spokesperson on AI Trust for clients, regulators, and industry forums, positioning the company as a leader in "Safe AI" operations.
• AI System of Record: Establish and maintain the "Source of Truth" for all AI assets—consolidating model registries, lineage, and audit trails.

2. AI Security & Defense (The "Secure" Mandate)

• Adversarial Resilience: Oversee AI red-teaming and stress testing to protect against prompt injection, model extraction, and data poisoning.
• Secure AI Lifecycle: Partner with the CIO to embed security into the LLMOps/DevSecOps pipeline, ensuring "Secure by Design" principles for agentic and autonomous systems.
• Data Sovereignty: Ensure RAG (Retrieval-Augmented Generation) and fine-tuning workflows do not result in PII leakage or cross-contamination of client data.
• Shadow AI Mitigation: Implement discovery and governance protocols to identify and secure unauthorized AI usage across business units.

3. Regulatory & Ethical Compliance

• Global Regulatory Radar: Ensure 100% compliance with the EU AI Act, NIST AI RMF, ISO 42001, and evolving state-level US laws (e.g., Colorado AI Act).
• Algorithmic Fairness: Mandate bias detection and mitigation protocols to ensure AI-driven business process decisions are equitable and transparent.
• Human-in-the-Loop (HITL): Define and enforce the "Human-in-the-loop" requirements for high-stakes operational tasks to prevent autonomous "drift" or "hallucination" damage.

4. Client & Operations Enablement

• Client Assurance: Support the "Growth Office" by participating in high-value client negotiations to provide transparency into how their data is protected within our AI ecosystem.
• Business Integration: Partner with Business Units to "RAI-enable" client workflows, ensuring that rapid automation does not bypass established risk guardrails.
• Third-Party Oversight: Lead the vetting process for foundation model providers (OpenAI, Anthropic, etc.) and open-source AI libraries to ensure they meet our security and ethical benchmarks.

5. Secure & Compliant AI Deployment

• Work with Architecture, Engineering, Data Platforms, and Solutions teams to ensure AI systems are built on secure, compliant, scalable, and governed platforms, supporting responsible deployment across use cases
• Ensure alignment with cloud, data governance, and platform modernization strategies

6. Enterprise AI Policy Implementation & Audits

• Oversee adherence to Responsible AI policies through periodic audits, monitoring dashboards, and compliance reviews
• Ensure readiness for internal and external assessments, including client driven AI governance evaluations‑driven AI governance evaluations

7. Capability Building and Culture Development

• Lead enterprise-wide evangelization, awareness and training sessions to build a culture of responsible AI use and risk-sensitive innovation
• Build and mentor a team comprising AI governance leads, risk specialists, AI ethicists, and security experts

Key Elements for the Role

• Experience: 15+ years of total professional experience in technical, legal, or risk leadership, with at least 5+ years of dedicated experience in AI/ML governance, security, or ethics.
• The "Hybrid" Expert: You must be able to discuss Transformer architectures and vector databases with engineers, and liability/indemnification with the Legal team.
• Regulatory Fluency: Deep familiarity with NIST AI RMF, ISO 42001, and the EU AI Act.
• Operational Depth: Proven experience in building a "Governance-as-a-Service" model in a global, highly regulated, or client-servicing enterprise
• Education: Bachelors in CS, Data Science, or Law/Ethics with a technical focus. Advanced degree (MS/PhD/JD) is highly preferred

Key Performance Indicators:

·      Framework Adoption: % of internal and client-facing models fully compliant with the NIST-aligned "Safe AI" framework.

·      Risk Mitigation: Zero "High" or "Critical" ethics/security incidents resulting from unvetted AI deployments.

·      Audit Readiness: Successful completion of third-party AI audits and certifications (e.g., ISO/IEC 42001).

·      Client Confidence: Qualitative "Trust Score" improvements in client surveys and successful closure of AI-dependent contracts.

Primary Internal Interactions:

• Senior Management Team
• Business Leadership and Functional Heads
• Analytics, Data Science, Digital and Technology Leaders
• CIO Office, General Counsel Office, Risk and Security Teams
• Enabling Functions – HR, Finance, Legal, Growth Office

Primary External Interactions

·      Regulatory bodies, industry forums, advisory councils

·      Service providers, solutions partners, audit firms, technology OEMs

·       Clients requiring AI assurance, transparency, and governance alignment