We are hiring a Technical Program Manager to lead technology delivery for one or more multi-year technology programs. This is a program leadership role for the AI era: you will translate strategy into executable plans, orchestrate large cross-domain delivery, manage program governance and risk, and serve as the primary point of contact for stakeholders across overall program leadership, Technology, Data, shared services, and other functional groups.

The TPM role is an unbiased leader focused on the technical execution of the program. You will not simply manage the program status 6 you will modernize how programs are managed across technology teams, embedding AI assistants, automation, and data-driven decision-making into governance, reporting, and delivery operations. You will operate as a direct partner for business program leadership & technology leaders, influence decisions at all levels, and help institutionalize consistent, AI-enabled program delivery practices across the organization.

Key Responsibilities:

• Drive and monitor end-to-end program technical execution: develop and maintain multi-year, multi-domain delivery plans that sequence technical work, integrations, and program increments.
• Serve as technology program manager: provide consistent, accurate, and timely program status, decisions, and delivery logistics to stakeholders and leadership.
• Run delivery operations: coordinate cutovers, command-center execution, hypercare, and handoffs to BAU/operations.

• Establish and run program governance (SteerCo, decision logs, RACI/RASCI matrices, stage gates) and ensure timely escalation and clear accountability for decisions OR support program governance and visibility in programs with an overall program leader from outside the technology organization.
• Own technology program risks: identify, quantify, and mitigate risks; maintain a RAID register; escalate proactively when delivery, timeline, or budget is threatened 6 before problems are realized, not after.
• Continuously map and manage dependencies across teams, domains, and portfolios; detect, communicate, and drive resolution of slips before they impact downstream commitments.
• Apply AI-powered analytics to program data to surface leading risk indicators, predict schedule variances, and enable earlier, better-informed interventions.

• Champion AI-enabled delivery: design, deploy, and continuously improve AI assistants and agents that automate program reporting, status synthesis, meeting summarization, RAID upkeep, and stakeholder communications.
• Demonstrate working AI fluency: understand generative AI concepts (LLMs, prompt engineering, RAG, agents, Model Context Protocol) well enough to evaluate use cases, shape responsible adoption, and engage credibly with engineering teams building AI solutions.
• Guide teams through the AI-augmented SDLC: understand how AI coding assistants, spec-driven development, and automated testing change delivery cadence, estimation, quality signals, and team composition.
• Apply responsible-AI judgment: ensure AI usage within the program aligns with enterprise standards for security, data privacy, explainability, and ethics.
• Model and mentor AI adoption: share reusable AI assets (assistants, prompts, playbooks) with the TPM community and coach teams and peers on effective, safe use of AI in daily delivery work.

• Track program tech financials (burn vs. plan), surface corrective actions, and report forecast vs. actuals.
• Define, collect, and report program delivery KPIs (leading and lagging), Agile/DevOps maturity metrics, team health, and quality indicators 6 increasingly through automated, AI-assisted dashboards rather than manual compilation.
• Tie program reporting to business outcomes (reliability, customer experience, value realized), not just activity and milestones.

• Build and maintain stakeholder management plans for technical execution; communicate trade-offs clearly; eliminate friction that impedes delivery.
• Present confidently to senior leadership, distilling complex technical and program information into clear insights that enable data-driven decisions.
• Partner closely with Overall Program Leads (OPLs), Product Management, Tech Leads, Architects, DevOps, Data, Security, Finance, and Procurement to ensure alignment and timely decisions.

• Engage with the enterprise TPM community to share best practices, contribute reusable playbooks and AI assets, and drive cross-program improvements.
• Play an active role in shaping how the delivery function evolves in the world of AI 6 piloting new ways of working and scaling what works.
• Operate independently: lead complex program workstreams with limited direction while escalating appropriately.

• 10+ years' experience delivering software solutions in an agile environment; experience leading large, complex, multi-year programs.
• Deep knowledge of Agile scaling practices and the ability to mobilize multiple agile teams across domains toward a shared mission.
• Strong technical fluency 6 able to engage credibly on architecture, integrations, cloud platforms, data/AI pipelines, and NFRs.
• Demonstrated AI proficiency: hands-on experience using generative AI tools (e.g., AI assistants, agents, copilots) to improve program execution, plus a working understanding of AI concepts sufficient to evaluate use cases and guide adoption.
• Experience with JIRA, Confluence, and SPM/portfolio tools; comfortable defining and enforcing tooling and automation standards.
• Demonstrated strength in governance, risk management, dependency mapping, and financial reporting (burn vs. plan).
• Data-driven decision-making: able to define metrics, interpret analytics, and use AI-generated insights while applying sound human judgment.
• Exceptional negotiation, facilitation, and consensus-building skills with cross-functional stakeholders.
• Highly developed interpersonal skills and executive presence; proven ability to influence without direct authority.
• Proven ability to operate with limited guidance and manage ambiguity in fast-evolving environments.
• Bachelor's or Master's degree in a technical or business discipline (or equivalent experience).

• Experience in property & casualty insurance or other regulated industries, including familiarity with responsible-AI, compliance, and data-governance considerations.
• Experience delivering AI/ML or data-platform programs, or embedding AI into the SDLC (AI-assisted development, testing, or operations).
• Background in DevOps, release orchestration, or technical delivery leadership.
• Relevant certifications: PMP, SAFe POPM/SPC, or equivalent; AI credentials such as Google Generative AI Leader, AWS Certified Cloud Practitioner / AWS AI Practitioner, or Microsoft AI Fundamentals are a plus.