AI Principal - Strategy & Transformation

Role Value Proposition

As a Principal on MetLife’s Delivery Strategy & Transformation (DST) team, you will set the direction for how Global Technology delivers products and software as it moves to an AI-First Operating Model. This is DST’s most senior individual-contributor role: enterprise breadth, accountability that runs end to end, and the latitude to define the approach with the standing to drive it through GT senior leadership. Assignments are agreed with the AVP and owned through to adopted practice.

About the team: DST is an individual-contributor team inside MetLife Global Technology, working directly with CIO organizations, Enterprise DevSecOps, Platform Engineering, and Enterprise Architecture. GitHub Enterprise and the agentic SDLC toolchain are being made productive now, and the AI-First Operating Model is being designed and proven in live delivery — this role shapes it rather than inherits it.

·What is changing: Global Technology is moving to an AI-first delivery model — agents performing delivery work alongside people, specifications and curated context replacing tribal knowledge, and review, traceability, and control points rebuilt around output that people and agents produce together.

·Why this role matters: the work of this team will redefine how teams plan, build, review, govern, and deliver technology in an AI-first environment — the roles people hold, the artifacts they produce, the evidence they leave behind, and the measures that show delivery actually improved. As DST’s most senior individual contributor, you set the direction of that change and carry it through to adopted practice across CIO organizations.

 • Work AI-first in your own practice — accelerating research, analysis, artifact production, and prototyping so one person covers ground that would otherwise require a team. As DST’s most senior individual contributor, your practice is the reference others are pointed to.

• Own the end-to-end agenda for assigned enterprise initiatives — target-state design, roadmap, success measures, governance, readiness, and adoption support — and carry them through with CIO organizations and delivery leaders. Accountability ends at measurable adoption, not at a recommendation.

• Take on the problems no single CIO organization can solve — undefined scope, contested ownership, several organizations that must change together — and convert them into a defined path with named owners, sequencing, and decision points.

• Put recommendations in front of GT senior leaders that move decisions — target-state options with cost, risk, capacity, and sequencing tradeoffs made explicit — and represent DST where delivery, architecture, risk, and platform priorities get reconciled.

• Partner with Enterprise DevSecOps, Platform Engineering, and Enterprise Architecture to make the GitHub Enterprise and agentic SDLC platform productive in practice — defining the workflow, role, and governance changes teams must make, and clearing the operating-model blockers platform capability alone cannot fix.

• Partner with CIO organizations, enterprise delivery leaders, portfolio organizations, and advisory teams to validate and improve enterprise operating models through real-world application — establishing feedback mechanisms that evaluate effectiveness, surface adoption insight, and determine where standards, governance, and guidance need adjustment.

• Shape the controls, guardrails, and evidence model for AI-assisted and agent-executed delivery with Risk, Audit, Legal, and Enterprise DevSecOps, so AI-generated work is traceable, reviewable, and defensible in a regulated environment.

• Lead stakeholder engagement, readiness, enablement, communications, and transition activities for DST-owned products, services, standards, and operating model changes, including the repeatable guidance and messaging leaders and teams work from. Partner with S&P and other stakeholders on broader enterprise change efforts.

• Advance enterprise delivery measurement — flow, engineering-effectiveness, and AI-specific indicators — and connect it to demonstrable business value rather than activity reporting.

• Hands-on experience with agentic AI frameworks in enterprise delivery — enough direct experience building, deploying, or governing agent-based workflows to judge where agents belong, what they can be trusted to do unsupervised, and how their use is governed at portfolio scale. Familiarity with AI assistants alone is not sufficient.

• 10+ years in enterprise technology delivery, transformation, operating-model design, or enterprise architecture.

• A track record of shaping how large organizations deliver products and software — not coaching individual teams — including the adoption, readiness, and stakeholder work that makes a change stick. Proven ability to define the path under ambiguity and advise senior leaders. Executive-grade written and verbal communication.

• Deep working knowledge of flow-based delivery systems and modern Agile ways of working — Scaled Agile (SAFe) or comparable frameworks, the product operating model, Lean and Kanban — with command of the end-to-end PDLC and SDLC as a single flow, and the judgment to determine what carries forward into an AI-first model.

• Experience designing governance and controls for AI-assisted delivery in a regulated environment — provenance and auditability, validation and human-accountability checkpoints, IP and licensing exposure, and the evidence risk and audit partners require.

The expected salary range for this position is $150,000 - $190,000. This role may also be eligible for annual short-term incentive compensation. All incentives and benefits are subject to the applicable plan terms.