Lead AI, Operating Model Design

MetLife; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

MetLife seeks a Lead, Operating Model Design within Global Technology to act as an internal consultant and operating model designer for an AI-First framework. You will author team archetypes, role definitions, accountability frameworks, and transition artifacts, then support execution through facilitation and delivery-leader feedback.

This specialist individual-contributor role shapes how CIO organizations plan, govern, and deliver AI-enabled work, defining standards, transitions, and end-to-end

Qualifications

• Hands-on experience with agentic AI frameworks and how to design roles, accountability, oversight for agent-participating delivery
• 8+ years in enterprise architecture or operating-model/organizational-design consulting, including regulated-enterprise experience
• Design of lifecycle architecture that reconciles with enterprise standards and platform constraints
• Experience designing governance, controls, and human-accountability models for regulated delivery
• Capability to defend design to CIO leadership and implementation teams

Responsibilities

• Author and maintain team archetypes and interaction patterns for AI-augmented delivery
• Define human-agent operating design with governance and escalation points
• Set design standards for consistent CIO organization adoption
• Collaborate with enterprise delivery leaders to incorporate field feedback and align improvements
• Produce reference implementation artifacts for CIOs to work from

Skills

Agentic AI frameworks

Enterprise architecture

Organizational design

Agile frameworks

Governance & controls

Tools

SAFe

Lean

Kanban

Job description

Role Value Proposition

As Lead, Operating Model Design, you will serve as an internal consultant and operating model designer for Global Technology’s AI-First operating model. You author the team archetypes, role and accountability frameworks, and transition-design artifacts that CIO organizations implement, then support execution through facilitation, process design, and feedback from delivery leaders. This is a specialist individual-contributor role: your impact comes from design that large organizations can adopt and keep using as tooling evolves.

The Opportunity

Role Value Proposition As Lead, Operating Model Design, you will serve as an internal consultant and operating model designer for Global Technology’s AI-First operating model. You author the team archetypes, role and accountability frameworks, and transition-design artifacts that CIO organizations implement, then support execution through facilitation, process design, and feedback from delivery leaders. This is a specialist individual-contributor role: your impact comes from design that large organizations can adopt and keep using as tooling evolves.

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 decision rights they carry, and the accountabilities that hold when an agent does the work. This role authors the design that change runs on, and the organizations implementing it work from what you produce.

Key Responsibilities

• Work AI-first in your own design practice — using AI to accelerate research, options analysis, artifact drafting, and stress-testing. Design credibility here depends on operating the way the target model expects others to operate.
• Author and maintain team archetypes and interaction patterns for AI-augmented delivery — team composition, AI integration level, and how teams interact across the delivery flow.
• Design role and accountability frameworks for the target operating model — role definitions, decision rights, skill expectations, and progression paths — aligned with the enterprise job family framework.
• Define the human-agent operating design — what people retain and what is delegated to agents, where human-above-the-loop review applies, and how accountability and escalation work when an agent acts — together with the governance and control points for agent-participating delivery, designed with Risk, Audit, Enterprise DevSecOps, and Platform Engineering.
• Set the design standards that keep operating-model decisions consistent across CIO organizations — when each archetype applies, what may be adapted locally, and where deviation requires approval — so organizations can make their own choices without escalating each one.
• Design the end-to-end lifecycle architecture that connects the PDLC and SDLC into one flow from product intent to running code, reconciled with MetLife Enterprise Architecture standards.
• Design the transition from today’s delivery model to the AI-First target state — sequencing, dependency mapping, and phasing, together with the stakeholder impacts, role transition paths, and enablement requirements each archetype creates.
• Collaborate with enterprise delivery leaders, portfolio organizations, and advisory teams to incorporate field feedback, evaluate model effectiveness, and align future-state improvements with practical delivery realities.
• Produce the reference implementation artifacts CIO organizations work from — decision-rights matrices, operating cadences, and worked examples of the model applied to a real delivery context — validated with delivery teams so adoption does not depend on interpreting the design.

Required Qualifications

• Hands‑on experience with agentic AI frameworks — how agents are configured, orchestrated, permissioned, and evaluated in real delivery workflows. You do not need to have built the platform, but you do need enough direct working experience to design roles, accountabilities, oversight models, and team archetypes for agent-participating delivery rather than describe them abstractly.
• 8+ years in enterprise architecture or operating-model / organizational-design consulting, including regulated-enterprise experience.
• Operating-model and role-framework design for large technology organizations, with design work that outlived a single tooling or methodology generation — and the command to defend that design to CIO leadership and the organizations expected to implement it.
• Design-level 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 — deep enough to take apart and rebuild, including where each breaks down under AI-augmented delivery, plus experience designing lifecycle architecture that reconciles with enterprise architecture standards and platform constraints.
• Experience designing governance, controls, and human-accountability models for regulated delivery — approval gates, decision rights, and evidence capture — including how agent-executed work is documented so risk and audit partners can review it.

Preferred Qualifications

• Adoption and readiness experience applied to structural change — role-transition design, stakeholder impact analysis, communication planning, and adoption sequencing — with designs that survived contact with the organizations expected to implement them.
• Experience working in a large enterprise organization of 1,000+ technologists and in regulated environments.
• Formal grounding in an organizational design, adoption, or change methodology — Team Topologies, sociotechnical systems design, Prosci, or equivalent — and experience defining