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Lincoln Financial

Insurance, retirement, and financial services provider

Lead AI Product Manager

Technical Product ManagementConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Three to ten years of experience in product management, product ownership, or a closely related role.
  • Hands-on experience working on AI, machine learning, or data-driven products, including direct collaboration with data science or engineering teams.
  • Familiarity with large language model concepts such as prompt engineering, model evaluation, and output quality assessment.
  • Experience with agile methodologies and backlog management tools such as Jira, Linear, or Productboard.
  • Ability to write clear, unambiguous user stories, product requirements documents, and feature specifications.
  • Bachelor's degree in Computer Science, Data Science, Business, or a related field.

Responsibilities

  • 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 sprint planning, standups, reviews, and retrospectives; keep delivery on track and surface blockers early.
  • Coordinate user acceptance testing, quality assurance, and launch readiness for AI feature releases, ensuring quality and compliance standards are met before launch.
  • Support the AVP in managing timelines, dependencies, and risks across feature workstreams.
  • Serve as the day-to-day product contact for business subject matter experts, engineering squads, and user experience designers within assigned AI feature areas.
  • Communicate feature status, trade-offs, and delivery risks to the AVP and relevant business partners.
  • Facilitate working sessions and backlog refinement meetings to drive team alignment and shared understanding of requirements.
  • Help business partners understand, test, and adopt new AI-driven capabilities as part of change management.
  • Apply responsible AI principles—including 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 internal governance and audit standards.
  • Collaborate with Trust & Safety, Legal, and Compliance teams as needed to support feature-level risk reviews.
  • 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 evaluations, user testing, and post-launch monitoring with the broader AI Product & Delivery team.
  • Partner with data scientists and machine learning engineers to understand model capabilities, limitations, and evaluation results for assigned AI features.
  • Assist in designing and executing evaluations for large-language-model-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 evaluation datasets, test case libraries, and regression frameworks to enable consistent model performance tracking.
  • Assist in prompt testing and iteration by running structured experiments to understand how prompt changes affect model behavior and output quality.
  • Help monitor model performance after launch and flag regressions or unexpected behavior to the data science team.

Desired Qualifications

  • Hands-on experience with large language model application programming interfaces or enterprise AI platforms such as Azure OpenAI, AWS Bedrock, Anthropic Claude, or Google Vertex AI.
  • Exposure to machine learning evaluation frameworks, annotation workflows, or AI observability tools such as LangSmith or Weights & Biases.
  • Familiarity with responsible AI practices, including bias detection, fairness evaluation, and model explainability.
  • Domain experience in life insurance, annuities, retirement planning, or employee benefits.
  • Product- or AI-related certifications, such as Pragmatic, AIPMM, data science, or machine learning-related certifications.

About the Company

Lincoln Financial

Insurance, retirement, and financial services provider

Lincoln Financial Group offers life insurance, annuities, and retirement income products through its network of affiliated companies, and also provides securities and investment advisory services via affiliated broker-dealers. Its products combine insurance coverage or retirement-focused contracts with investment options, where customers fund premiums, choose subaccounts or riders, and receive benefits such as death benefits, living benefits, or guaranteed income in retirement. The company differentiates itself with a family of affiliated brands and distributors that coordinate life, annuity, and advisory products under one umbrella. Its goal is to help individuals and families protect loved ones, plan for retirement, and achieve financial security through integrated protection and investment solutions.

Company size
Not listed
Company stage
Not listed
Total funding
$128.8M
Headquarters
Radnor Township, Pennsylvania
Founded
1905

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