Product Owner, AI Platform & Delivery - LMI

Product Owner, AI Platform & Delivery - LMI Job Locations US-MA-Boston | US-NY-New York ID 2026-76343 Position Type Full-Time Job Grade 62 Department 043D-14402 GIS-AI Collective Market Liberty Mutual Investments (LMI) Referral Bonus Amount 2500.00 Minimum Salary USD $90,000.00/Yr. Maximum Salary USD $180,000.00/Yr. Recruiter Kaitlan Rice Referral Bonus Eligible? Yes Description Description We’re looking for a Product Owner, AI to join Liberty Mutual Investments’ (LMI) AI team. Reporting to the Director of LMI’s AI Lab, you’ll own backlog prioritization, delivery coordination, and continuous improvement across a portfolio of live AI capabilities — including MCP connectors, document ingestion pipelines, and platform enablement across the firm. Deep expertise in generative AI is not a prerequisite — the field is still maturing, and we invest in developing that expertise. What matters is a proven track record in product ownership and delivery, and the drive to develop genuine expertise in how these tools work.

LMI’s AI Lab spans the full lifecycle of AI capabilities, from early exploration and validation through production deployment and ongoing maintenance. You’ll drive backlog prioritization in close partnership with the Director, lead delivery coordination with technology partners, and ensure AI solutions continue to meet the evolving needs of investment teams. This is a high-visibility role at the intersection of frontier AI and institutional investment workflows — with real production systems, active governance processes, and a multi-team stakeholder environment that requires someone who can operate independently from day one.

What You’ll Do Product Backlog & Delivery Coordination

• Own and drive the AI Lab backlog across MCP connectors, document ingestion pipelines, platform enablement, and additional workstreams — prioritizing in close alignment with the Director.
• Translate validated prototypes into structured product requirements, including acceptance criteria, integration needs, and deployment considerations for the engineering team.
• Lead delivery timelines, dependencies, and stakeholder communication across Technology, Security, and Investment teams.
• Track progress against delivery milestones and escalate blockers, risks, and scope changes early.

Production Quality & User Feedback

• Monitor production solution health, including usage metrics, user feedback, support issues, and quality signals, and drive iterative improvements in alignment with team priorities.
• Coordinate user acceptance testing for new capabilities and enhancements, ensuring solutions meet business requirements before rollout.
• Maintain documentation, release notes, and usage guidance for production AI assets.
• Identify patterns in user feedback and support requests that signal gaps in current capabilities and translate those insights into structured opportunities for the team to explore. Governance & Enablement
• Own end-to-end coordination of Responsible AI Committee (RAIC) submissions and security review for new AI capabilities and platform features, serving as the primary point of contact across governance stakeholders. Qualifications Required
• Bachelor’s degree in business, finance, technology, or a related field.
• 3–5 years of experience in product ownership, business analysis, technology-enabled solutions, or a related role in financial services.
• Ability to translate business needs into structured requirements and acceptance criteria for engineering teams.
• Excellent communication and interpersonal skills, with comfort working across Technology, Investment, and Governance teams.
• Strong organizational and problem-solving skills, including the ability to manage competing priorities, track multiple workstreams, and keep delivery on course. Preferred
• Experience working in or alongside investment teams in financial services or asset management.
• Exposure to AI/ML concepts or enterprise AI tools (e.g., Claude, ChatGPT, Copilot) and curiosity about how they apply to business workflows.
• Interest in or exposure to applied AI infrastructure concepts such as agentic workflows, retrieval-augmented generation (RAG), and tool-use protocols (e.g., MCP).
• Familiarity with product management practices,bincluding backlog management, user story writing, and agile delivery.
• Experience with enterprise data platforms (e.g., Snowflake, Databricks) or similar tools.
• Experience supporting change management and adoption of new tools and processes. Qualifications asdf

Employees should review all role requirements and apply only for positions for which they are eligible. Hiring processes may vary by country, including differences in procedures, requirements, and timelines. For country-specific details, please consult your local recruiting / HR team.

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