AI Product Manager

Alternate Locations:
Radnor, PA (Pennsylvania);
Greensboro, NC (North Carolina)

Work Arrangement:

Hybrid :
Employee will work 3 days a week in a Lincoln office

Relocation assistance: is not available for this opportunity.

Requisition #: 76401

The Role at a Glance

Lincoln Financial Group is seeking a detail-oriented and delivery-focused Product Owner to join our AI Product & Delivery organization. In this role, leading innovation squads, you will own the day-to-day execution of AI product features and capabilities within an assigned product domain, working hands-on with data science, engineering, and business domain teams to bring AI solutions from backlog to production. Reporting to the VP/AVP of AI Products, you will serve as the connective tissue between business process reimagination and technical delivery - writing clear user stories, managing sprint-level priorities, supporting model evaluations, and ensuring AI features meet quality, compliance, and user experience standards.

This role is ideal for a practitioner who thrives in the details and is eager to grow their AI product career in a regulated financial services environment.

What you'll be doing

AI Feature Ownership & Delivery

* Own and maintain the product backlog for assigned AI features or squads, ensuring stories are well-defined, prioritized, and ready for sprint execution.

* Write detailed user stories, acceptance criteria, and feature specifications for AI-driven capabilities in collaboration with engineering and data science teams.

* Lead actively in agile ceremonies - sprint planning, standups, reviews, and retrospectives - keeping delivery on track and surfacing blockers early.

* Coordinate UAT, QA, and launch readiness activities for AI feature releases, ensuring quality and compliance standards are met before go-live.

* Support the AVP in managing timelines, dependencies, and risks across feature work streams.

Stakeholder Engagement

* Serve as the day-to-day product contact for business SMEs, engineering squads, and UX designers within assigned AI feature areas.

* Communicate feature status, trade-offs, and delivery risks clearly to the AVP and relevant business partners.

* Facilitate working sessions and backlog refinement meetings to drive team alignment and shared understanding of requirements.

* Support change management by helping business partners understand, test, and adopt new AI-driven capabilities.

Responsible AI & Compliance

* Apply responsible AI principles - fairness, transparency, explainability, and privacy - in the definition and acceptance of AI features.

* Escalate potential compliance, bias, or safety concerns identified during model evaluation or feature review to the AVP and relevant risk partners.

* Ensure AI feature documentation, testing evidence, and release artifacts meet Lincoln's internal governance and audit standards.

* Collaborate with Trust & Safety, Legal, and Compliance teams as needed to support feature-level risk reviews.

Performance & Insights

* Define and track feature-level success metrics including adoption, task completion, model accuracy, and user satisfaction.

* Analyze usage data, model performance logs, and user feedback to identify improvement opportunities and inform backlog prioritization.

* Contribute to sprint-level reporting and help maintain product dashboards that surface key delivery and quality metrics.

* Share learnings from evals, user testing, and post-launch monitoring with the broader AI Product & Delivery team.

Data Science & Model Evaluation Support

* Partner with data scientists and ML engineers to understand model capabilities, limitations, and evaluation results for assigned AI features.

* Assist in designing and executing evaluations (evals) for LLM-powered features - assessing output quality, accuracy, relevance, and safety against defined benchmarks.

* Review and annotate model outputs as part of human-in-the-loop feedback processes, identifying failure modes, edge cases, and opportunities for improvement.

* Support the creation of eval datasets, test case libraries, and regression frameworks to enable consistent model performance tracking.

* Assist in prompt testing and iteration - running structured experiments to understand how prompt changes affect model behavior and output quality.

* Help monitor model performance post-launch and flag regressions or unexpected behavior to the data science team.

What we're looking for

Must-have (required)

* 3-10 years of experience in product management, product ownership, or a closely related role.

* Hands-on experience working on AI, ML, or data-driven products - including direct collaboration with data science or engineering teams.

* Familiarity with LLM concepts such as prompt engineering, model evaluation, and output quality assessment.

* Experience with agile methodologies and backlog management tools (e.g., Jira, Linear, Productboard).

* Strong written communication skills - able to write clear, unambiguous user stories, PRDs, and feature specifications.

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