Senior Program Manager – AI/ML Governance

GiGa-Ops Global Solutions is seeking a highly experienced Senior Program Manager with AI/ML expertise to lead enterprise-wide AI governance, risk management, and regulatory compliance initiatives. The role focuses on Responsible AI, Generative AI, and Agentic AI systems, ensuring compliance with global AI regulations—especially the EU AI Act, while championing privacy-by-design and data protection across AI initiatives.

Responsibilities:

• Lead and operationalize AI governance, compliance, and risk programs across the enterprise
• Design and maintain an enterprise AI governance framework
• Define Responsible AI policies (bias mitigation, explainability, hallucination control, prompt-injection defenses)
• Establish controls for Agentic AI and multi-agent orchestration
• Drive EU AI Act readiness and manage compliance activities
• Perform AI risk classification, conformity assessments, and audits
• Maintain model inventory, validation, and documentation for regulatory evidence
• Lead privacy and data protection activities related to AI: conduct Data Protection Impact Assessments (DPIAs) for high-risk systems, ensure data subject rights are supported, and apply data minimization and pseudonymization where appropriate
• Oversee third-party and vendor risk for AI models and data processors, ensuring contracts include required data processing and auditing clauses
• Maintain auditable records, evidence retention policies, and coordinate incident and breach reporting to internal stakeholders and regulators as required
• Govern Azure AI services (access control, RBAC, managed identities, key management, content safety)
• Ensure data protection, encryption, PII handling, and audit traceability
• Implement privacy-by-design and secure data lifecycle practices: data residency controls, secure pipelines, retention policies, and appropriate data-sharing agreements
• Collaborate with cloud security and privacy teams to validate controls, logging, and monitoring that support regulatory evidence and compliance audits
• Define KPIs and dashboards to monitor AI risk, performance, and cost
• Provide executive reporting and maintain governance metrics for stakeholders
• Establish compliance and privacy metrics (e.g., DPIA coverage, remediation status, audit findings, incident response SLAs) and integrate these into regular reporting cycles
• Maintain processes for breach detection, escalation, regulator reporting, and post-incident remediation tracking
• Assess and reconcile AI governance, policies, and processes after acquisitions
• Harmonize workflows, remove overlaps, and enable consolidated governance operations
• Embed governance into Architecture Review Board (ARB) and intake workflows
• Improve AI intake processes (Agentic AI, ERAG, other governance gates) and maintain a use-case inventory
• Provide operational support through an AI Governance mailbox and ticketing integration
• Collaborate with Legal, Compliance, Engineering, Product, and Security to operationalize policies
• Design and deliver Responsible AI and regulatory training for cross-functional teams

Requirements:

• 8+ years – Program Management, Risk, or Compliance roles with exposure to AI or Technology Governance
• 3+ years – AI/ML lifecycle knowledge, including Generative AI (GenAI)
• 2+ years – Ethical & Responsible AI principles (accountability, explainability, fairness, transparency)
• 2+ years – AI regulatory frameworks, including EU AI Act, NIST AI RMF, GDPR, and OECD AI Principles
• 5+ years – Post-merger integration and governance/process reconciliation
• 1–2 years – Policy definition for GenAI and Agentic AI systems
• 1–2 years – AI risk assessment, mitigation strategy, and model lifecycle management
• 2–3 years – AI governance framework design or execution
• Strong stakeholder management and communication skills
• Excellent verbal and written communication
• Strong stakeholder and interpersonal skills
• Analytical and problem-solving mindset
• Experience in Agile/Scrum environments
• Hands-on experience with Jira or Azure DevOps
• Proactive status reporting and ownership mindset
• Experience in regulated or global enterprise environments
• Exposure to Architecture Review Boards and governance councils
• Certifications in AI Ethics, Compliance, or Risk Management