AI - Agile Coach / AI Strategy & Governance

Job Description:

Key Responsibilities

• Lead the rollout and adoption of AI Strategy and Governance frameworks across Services.
• Coach teams and leaders on AI Product Development Lifecycle (PDLC) and AI-enabled delivery practices.
• Establish governance processes, controls, and execution mechanisms for AI initiatives.
• Develop and operationalize AI delivery playbooks, standards, and best practices.
• Facilitate training, enablement, and change management activities across stakeholder groups.
• Define and implement metrics, measurement frameworks, and reporting mechanisms.
• Support the design and evolution of the AI operating model.
• Partner with executive stakeholders to drive alignment, adoption, and organizational change.
• Provide hands-on coaching and implementation support rather than purely advisory guidance.

Required Experience

Agile & Delivery Leadership

• Extensive Agile coaching experience.
• Strong SAFe (Scaled Agile Framework) implementation experience.
• Demonstrated success leading large-scale Agile transformations.

AI Product Development Lifecycle (Critical)

• Hands-on experience implementing AI PDLC frameworks and governance practices.
• Practical experience integrating AI lifecycle controls into delivery processes.
• Understanding of AI risk management, governance, compliance, and responsible AI considerations.

Program Management (Critical)

• Strong program management background.
• Proven ability to independently manage complex workstreams with minimal oversight.
• Experience coordinating multiple stakeholders, dependencies, and organizational initiatives.

Executive Stakeholder Management

• Experience working directly with senior leaders and executives.
• Ability to influence, facilitate decisions, and drive adoption across large organizations.
• Excellent communication, facilitation, and change leadership skills.

Areas of Initial Focus

1. AI PDLC / SDLC Frameworks
2. Program Management Practices
3. AI Governance Playbook Development
4. Training, Enablement, and Rollout
5. Metrics, Measurement, and Reporting
6. AI Operating Model Design and Implementation