AI Technical Program Manager

Liberty Mutual•Portsmouth, NH

3d•Hybrid

About The Position

Liberty Mutual Technology's Global Digital Services organization is seeking a highly skilled and experienced Technical Program Manager (TPM) to lead program delivery for the AI Backbone, Liberty Mutual's shared enterprise foundation for AI. This role will focus on driving alignment, execution, and adoption across a broad ecosystem of stakeholders as the organization continues to expand and mature AI capabilities across the enterprise. The AI Backbone provides the shared capabilities, standards, and reusable services that enable teams across Liberty Mutual to build and deploy AI solutions consistently, securely, and efficiently. Rather than having individual teams create their own approaches to security, governance, observability, identity, and AI operations, the Backbone establishes a common foundation that accelerates delivery while reducing complexity and risk. Supporting a broad spectrum of AI use cases, from generative AI applications to advanced agentic systems, the Backbone is designed to evolve alongside the rapidly changing AI landscape. It brings together shared technical capabilities, enterprise platforms, governance, and delivery partnerships to accelerate innovation, reduce risk, and enable AI adoption across Liberty Mutual. The TPM joining this program will play a pivotal role in helping Liberty Mutual realize the full potential of AI as an enterprise capability. Working across a diverse ecosystem of technology, data, security, architecture, finance, and business stakeholders, this leader will drive alignment around shared priorities, informed decision-making, and the successful adoption of the capabilities, standards, and operating models that enable AI at scale. This is a highly visible role with the opportunity to influence how Liberty Mutual scales and governs AI across the enterprise. The successful candidate will bring clarity and momentum to a rapidly evolving landscape, helping leaders make informed decisions while aligning efforts across teams, platforms, and strategic initiatives. Success in this role requires exceptional program leadership, strong executive presence, and the ability to influence across a highly matrixed organization. The ideal candidate combines strategic thinking with technical curiosity and is comfortable engaging leaders across engineering, security, architecture, data, and business domains to translate enterprise AI strategy into coordinated action and measurable outcomes.

Requirements

Bachelor's or master's degree in a technical or business discipline, or equivalent experience.
Minimum 12+ years of technical program management, enterprise transformation, or implementation consulting experience, including 5+ years leading multi-organization, multi-year technology programs in an agile environment.
Demonstrated ownership of an enterprise platform, shared-services, or foundational capability program (e.g., cloud platform, data platform, identity, developer enablement, or AI/ML platform) where success depended on adoption by teams outside your reporting line.
Working technical fluency in modern AI and agentic architectures: LLM access and model gateways, agent runtimes and orchestration, memory and semantic layers, evaluation and observability, and identity and governance controls.
Familiarity with AWS Bedrock / AgentCore, Databricks / MLflow, Snowflake, Azure Entra ID, Datadog, and MCP / A2A interoperability standards is strongly preferred.
Proven experience establishing portfolio governance – decision forums, readiness criteria, RACI, escalation frameworks and executive scorecards – across organizations that do not report to you.
Track record of regular, high-quality communication with C-level and ELT-level technology leadership, including structuring options and investment asks and driving decisions in contentious settings.
Experience with technology financial management: FinOps, rent / buy / build economics, business cases, capacity planning and value realization tracking.
Demonstrated leadership of organizational change in large technology organizations, moving teams from local autonomy toward shared standards while preserving delivery velocity.
Exceptional ability to drive and achieve major transformational outcomes through influence, without direct reporting authority, across engineering, architecture, security, data, finance and business-unit leaders.
Strong analytical skills and comfort creating and leveraging data (readiness metrics, adoption metrics, dependency and risk density) to drive decision-making.
Experience coaching or setting standards for other program managers or TPMs; ability to raise the execution bar across a practice.
Proficiency in developing structured, impactful executive presentations and written narratives.
Continual knowledge of the evolving AI and technology landscape, internal and external, to shape solutions with technical longevity.
In-depth knowledge of IT concepts, strategies and methodologies and their application to business opportunities; in-depth knowledge of agile methodology and the ability to mobilize multiple delivery teams across multiple domains toward a single mission.
Highly developed negotiation, facilitation and consensus-building skills demonstrated through effective interactions with cross-functional stakeholders.

Nice To Haves

Familiarity with AWS Bedrock / AgentCore, Databricks / MLflow, Snowflake, Azure Entra ID, Datadog, and MCP / A2A interoperability standards is strongly preferred.

Responsibilities

Coordinating the planning, governance, and execution required to advance the AI Backbone and enable consistent adoption of shared AI capabilities across Liberty Mutual.
Bringing together stakeholders across technology and business domains, helping leaders make informed decisions, manage dependencies, and translate strategic priorities into measurable outcomes.
Developing and owning the multi-year AI Backbone roadmap (Now / Next / Later), sequencing work across shared capabilities, contributing teams, and strategic initiatives.
Defining target outcomes, phase milestones, and readiness criteria while adapting plans as technologies, priorities, and enterprise needs evolve.
Guiding the evolution of the Backbone operating model from managed reuse toward federated adoption.
Maintaining an integrated program plan and delivery rhythm across workstreams, actively managing dependency health, milestone slippage, and re-sequencing as conditions change.
Leading cross-functional planning, prioritization, and decision forums spanning Global Digital Services (GDS), Global Cyber Security (GCS), Enterprise Data & Data Science (ED&DS), Enterprise Architecture, Enterprise Observability, Finance, and lighthouse delivery teams.
Fostering shared accountability without direct reporting authority and establishing consistent planning, reporting, and governance practices across participating teams.
Setting the execution quality bar for program and project leads working on AI initiatives across domains, and coaching them toward consistent planning, risk, and reporting practices.
Coordinating strategic technology partners including AWS, Databricks, Snowflake, Microsoft, Datadog, and Zscaler across evaluation, commitment, and scale-out decisions.
Ensuring build, buy, and partner strategies align with enterprise priorities, timelines, commercial objectives, and quality expectations.
Driving adoption of shared AI capabilities, approved patterns, and production-readiness standards across teams with varying priorities, business needs, and risk profiles.
Partnering across the organization to promote consistent approaches to AI delivery while establishing governance mechanisms that support long-term adoption and scale.
Proactively identifying systemic and cross-program risks spanning identity, governance, model risk, data access, security, and cost.
Partnering with GCS, ED&DS, LibertyAIR, Enterprise Architecture, and other stakeholders to address risks before they become barriers to adoption or scale.
Maintaining an enterprise view of risk and dependency health across the AI Backbone portfolio.
Serving as the primary author and presenter of AI Backbone updates for Tech ELT, SLT, and business leadership.
Translating complex technical concepts, program progress, tradeoffs, and investment decisions into clear, decision-oriented communications and executive-level narratives, including progress-to-goal, decisions required, and risks surfaced ahead of impact.
Identifying opportunities to simplify, automate, and mature the Backbone operating model, reducing manual effort associated with onboarding, readiness assessment, governance, and reporting.
Capturing lessons learned and emerging best practices and incorporating them into reusable patterns, standards, and operating rhythms.
Designing and operating the governance model for the AI Backbone, including decision frameworks, escalation paths, production-readiness criteria, ownership models, and executive scorecards.
Shifting governance discussions from status reporting to informed decision-making.
Building and maintaining visibility into dependencies across shared capabilities, strategic AI initiatives, and underlying enterprise platforms.
Maintaining an inventory of AI and agentic initiatives, track maturity and readiness, and help resolve ownership ambiguity across teams and domains.
Partnering with Technology & Enterprise Finance and Strategy & Transformation to support AI FinOps, investment planning, capacity management, funding requests, and value realization metrics.
Providing leaders with the information needed to make informed investment decisions and prioritize resources effectively.
Participating in architecture and design forums to understand tradeoffs across shared capabilities and platforms, and using that understanding to inform sequencing, readiness criteria, and risk assessment.
Bringing structure to ambiguity, framing complex cross-organizational challenges, and guiding stakeholders toward aligned decisions.
Intervening based on program-level impact rather than task-level detail, letting capability and lighthouse teams own their execution while maintaining visibility into decisions, dependencies, and risks.
Regularly advising and being accountable to Liberty Mutual's senior technology leaders and providing clear, actionable insights that inform strategy, prioritization, and investment decisions.
Measuring success by alignment across stakeholders, consistency of execution, and the overall health and adoption of the AI Backbone, measured through adoption, readiness, and stakeholder confidence metrics rather than the delivery of any single workstream.