Head of AI-Enabled Engineering Transformation

JPMorgan Chase & Co.•Jersey City, NJ

About The Position

Join Employee Platforms as the Head of AI‑Enabled Engineering Transformation, a senior leadership role accountable for driving the execution of our AI‑first vision for our Engineers. This role owns the transformation program that accelerates AI adoption, improves developer efficiency, modernizes team constructs, and ensures measurable business value. You will operate at the intersection of technology strategy, engineering execution, talent transformation, and change management—working with senior leaders, product lines, and global engineering teams to embed AI and agentic ways of working into how we design, build, and operate software.

Requirements

Senior technology leadership experience driving large‑scale transformation programs.
Deep understanding of modern software engineering, SDLC, and developer productivity metrics.
Hands‑on familiarity with AI‑assisted development tools (e.g., GitHub Copilot, Claude Code) and agentic concepts.
Experience operating in regulated enterprise environments with strong governance expectations.
Strong program leadership skills—roadmaps, dependency management, metrics, and execution rigor.
Ability to influence across engineering, product, HR, risk, and executive leadership.
Exceptional communication skills with the ability to translate strategy into action.

Nice To Haves

Experience leading AI or digital transformations within large engineering organizations.
Background in enterprise platforms, developer experience, or productivity tooling.
Exposure to agentic systems, advanced IDEs, or autonomous workflow orchestration.
Proven success driving cultural change and adoption at scale.
Experience working across global teams and delivery centers.

Responsibilities

Lead the end‑to‑end AI‑Enabled Teams transformation program for Employee Platforms, translating vision into executable workstreams with clear outcomes and KPIs.
Own developer efficiency strategy, including interventions that improve velocity, quality, and cost.
Drive large‑scale AI adoption across engineering teams, including coding assistants, agent‑assisted workflows, and emerging autonomous capabilities.
Partner with Architecture, Security, Risk, and AI governance teams to ensure compliant, secure, and responsible AI usage.
Modernize engineering operating models and team design for an agent‑augmented world, including POD experiments and new delivery constructs.
Lead job family normalization and talent alignment to ensure engineers are mapped, measured, and developed appropriately.
Shape hiring practices and AI talent standards, including AI bar raisers, role definitions, and skills expectations.
Establish education, enablement, and gamification programs to institutionalize AI‑native engineering behaviors.
Engage and influence MD, ED, and VP leadership to drive mindset shift, accountability, and sustained change.
Report progress, risks, and outcomes to senior leadership with clear, data‑driven narratives.