Job Description

Lead IAM’s transition to AI-native and agent-enabled ways of working. Turn high-value opportunities into measurable improvements in quality, speed, precision, and business impact.

As an Applied AI Transformation Director-Identity Access Management  within Identity and Access Management in the Chief Technology Office, you will translate IAM’s AI strategy into sustained organizational change and measurable outcomes. You will work across IAM functions to identify and prioritize opportunities, lead multidisciplinary teams through applied AI initiatives, and establish repeatable practices that embed AI into day-to-day work.

This senior individual-contributor player-coach role combines hands-on applied AI delivery, organizational transformation, practitioner coaching, and executive counsel. You will independently lead the integrated execution of IAM’s applied AI transformation portfolio within agreed strategic direction. You will work directly with teams to frame problems, build and evaluate practical solutions, develop practitioner capability, and scale validated approaches. You will advise senior leadership on priorities, delivery risks, investment choices, and the evolution of IAM’s AI-enabled operating model.

Job Responsibilities

• Translate IAM’s AI strategy into a prioritized portfolio of measurable transformation outcomes across business and technology functions.
• Partner with function leaders to drive AI-native adoption through direct engagement, coaching, experimentation, and capability development.
• Identify and prioritize high-value opportunities, define target outcomes, and lead multidisciplinary applied AI initiatives from discovery through validated results.
• Establish practical guardrails, repeatable methods, decision forums, and adoption pathways that enable responsible AI use at scale across IAM.
• Lead applied AI outcomes that rely on shared data, context, platform services, and specialist expertise, coordinating delivery with accountable capability owners.
• Modernize selected IAM workflows through intelligent automation, applied AI, and redesigned human-agent interaction, with clear measures of quality, efficiency, control, and business impact.
• Build practitioner capability across IAM by translating emerging AI capabilities into practical guidance, reusable methods, and sustainable working practices.
• Establish the shared measurement method for adoption, effectiveness, and value realization, and integrate function-owned evidence into an IAM-wide view of outcomes, risks, and dependencies.
• Advise senior leadership on applied AI opportunities, operating-model implications, investment priorities, and delivery risks, and resolve cross-functional barriers to execution.

Required Qualifications, Capabilities, and Skills

• Extensive experience leading applied AI transformation in large, complex organizations, with direct accountability for delivering measurable outcomes across multiple functions.
• Demonstrated hands-on depth designing, prototyping, and evaluating solutions using generative AI, large language models, agentic systems, retrieval-augmented generation, and context engineering, including human oversight and evaluation of non-deterministic systems.
• Demonstrated experience identifying, validating, and prioritizing applied AI opportunities through measurable experiments and progressing successful concepts into scalable capabilities.
• Proven experience mobilizing multidisciplinary teams through the full delivery lifecycle, including problem definition, prototyping, evaluation, governance, implementation, adoption, and benefits realization.
• Demonstrated success coaching technical and non-technical practitioners, building applied AI capability, and establishing repeatable methods that teams can adopt independently.
• Experience leading organizational transformation or operating-model change through influence in a matrixed environment, including stakeholder alignment, adoption planning, resistance management, and sustained behavioral change.
• Exceptional communication, judgment, and influencing skills, with the ability to translate AI capabilities, technical trade-offs, risks, and business priorities across executive, product, engineering, data, operations, risk, and control audiences.

Preferred Qualifications, Capabilities, and Skills

• Experience in financial services or another regulated, control-intensive environment, including familiarity with responsible AI, model risk, data governance, privacy, and audit requirements.
• Working knowledge of identity and access management, privileged access, secrets management, entitlements, or policy-controlled automated actions.
• Experience scaling applied AI solutions across multiple teams using shared data, knowledge, context, or self-service capabilities.
• Experience evaluating internal and third-party AI capabilities and shaping build, partner, adopt, or defer recommendations based on value, maturity, integration, risk, and lifecycle considerations.
• Bachelor’s or advanced degree in Computer Science, Data Science, Engineering, Business, or a related discipline, or equivalent practical experience.