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About This Role
Date: Sep 28, 2026
Primary Location: Radnor, PA, US
Company: Lincoln Financial
Alternate Locations: Radnor, PA (Pennsylvania); Charlotte, NC (North Carolina); Fort Wayne, IN (Indiana); 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 #: 76685
The Role at a Glance
Lincoln Financial is expanding its AI Product & Delivery organization and is seeking an AVP, AI Product Management to help drive execution of high impact AI initiatives across the enterprise.
In this role, you will own AI product strategy and delivery within defined business domains, translating advanced AI capabilities into scalable, responsible solutions that deliver measurable business value. Reporting to senior AI product leadership, you will play a critical hands on role in bringing AI from concept to production in a highly regulated financial services environment, partnering closely with business leaders, data science, engineering, design, and risk teams.
This is an ideal opportunity for an experienced AI product leader who thrives in ambiguity, balances strategy with execution, and is passionate about responsible innovation.
What you'll be doing
AI Product Strategy & Execution
- Own end to end product strategy and roadmaps for a portfolio of AI initiatives aligned with Lincoln’s priorities across insurance, annuities, and retirement solutions.
- Identify, validate, and refine high value AI use cases through stakeholder engagement, customer insights, data analysis, and experimentation.
- Translate emerging AI capabilities—including LLMs, agentic workflows, and multimodal AI—into practical product solutions with clear business outcomes.
- Prioritize product backlogs by balancing impact, feasibility, regulatory considerations, and user experience.
- Contribute to broader AI product portfolio strategy in partnership with VP and SVP leadership.
- Serve as a subject matter expert and product thought leader within assigned AI domains.
Cross Functional Delivery
- Lead agile product delivery for AI initiatives in close partnership with data science, engineering, UX, and business SMEs.
- Develop clear product feature requirements, user stories, success metrics, and release plans for AI driven capabilities.
- Guide teams through the ambiguity inherent in AI product development while maintaining strong delivery momentum.
- Manage timelines, dependencies, risks, and tradeoffs to ensure high quality, on time delivery.
- Coordinate across business units—including Annuities, Life Insurance, Retirement, and Group Protection—to tailor solutions to domain specific needs.
Stakeholder Engagement & Change
- Act as a primary product point of contact for business stakeholders and technology partners within assigned initiatives.
- Communicate product vision, progress, tradeoffs, and outcomes clearly to leaders across levels.
- Facilitate roadmap reviews, working sessions, and design thinking workshops to drive alignment and shared ownership.
- Support change management by enabling business partners to adopt and operationalize AI driven capabilities.
Responsible AI & Governance
- Embed responsible AI principles—fairness, transparency, explainability, and data privacy—into all product decisions.
- Partner closely with Legal, Compliance, Risk, and Enterprise Governance teams to ensure regulatory alignment (e.g., NAIC, SEC/FINRA).
- Ensure AI products meet internal governance, documentation, and monitoring requirements throughout the lifecycle.
Performance & Insights
- Define and track KPIs and OKRs, including adoption, efficiency gains, model performance, and customer impact.
- Use data, experimentation, and user feedback to continuously improve product performance.
- Contribute to business cases, benefits tracking, and ROI analyses for AI investments.
- Share learnings and best practices across the AI Product & Delivery organization.
What we’re looking for
Must Haves
- 8+ years of product management experience, including 3+ years focused on AI, ML, or data driven products.
- Proven experience delivering AI/ML powered products from concept through production.
- Strong understanding of machine learning fundamentals, generative AI, NLP, and modern AI development lifecycles.
- Experience working in financial services, insurance, fintech, or other regulated industries.
- Demonstrated ability to influence and align cross functional teams in a matrixed environment.
- Excellent written and verbal communication skills with the ability to translate technical concepts for business audiences.
- Bachelor’s degree in Computer Science, Engineering, Business, or a related field.
Nice to Haves
- Hands on experience with LLM based solutions, agentic systems on enterprise AI platforms (e.g., Azure OpenAI, AWS Bedrock, Google Vertex AI).
- Familiarity with MLOps, model monitoring, evaluation techniques, and responsible AI frameworks.
- Domain experience in life insurance, annuities, retirement planning, or employee benefits.
- MBA or advanced degree in a technical or analytical discipline.
- Product or AI related certifications (e.g., Pragmatic, AIPMM, data science or ML credentials).
Application Deadline
Applications for this position will be accepted through November 30, 2026, subject to earlier closure due to applicant volume.
What’s it like to work here?
At Lincoln Financial, we love what we do. We make meaningful contributions each and every day to empower our customers to take charge of their lives. Working alongside dedicated and talented colleagues, we build fulfilling careers and stronger communities through a company that values our unique perspectives, insights and contributions and invests in programs that empower each of us to take charge of our own future.
What’s in it for you:
- Clearly defined career tracks and job levels, along with associated behaviors for each of Lincoln's core values and leadership attributes
- Leadership development and virtual training opportunities
- PTO/parental leave
- Competitive 401K and employee benefits
- Free financial counseling, health coaching and employee assistance program
- Tuition assistance program
- Work arrangements that work for you
- Effective productivity/technology tools and training
The pay range for this position is $171,375 - $274,200 with anticipated pay for new hires between the minimum and midpoint of the range and could vary above and below the listed range as permitted by applicable law. Pay is based on non-discriminatory factors including but not limited to work experience, education, location, licensure requirements, proficiency and qualifications required for the role. The base pay is just one component of Lincoln’s total rewards package for employees. In addition, the role may be eligible for the Annual Incentive Program, which is discretionary and based on the performance of the company, business unit and individual. Other rewards may include long-term incentives, sales incentives and Lincoln’s standard benefits package.
About The Company
Lincoln Financial (NYSE: LNC) helps people to confidently plan for their version of a successful future. We focus on identifying a clear path to financial security, with products including annuities, life insurance, group protection, and retirement plan services.
With our 120-year track record of expertise and integrity, millions of customers trust our solutions and service to help put their goals in reach.
Lincoln Financial Distributors, a broker-dealer, is the wholesale distribution organization of Lincoln Financial. Lincoln Financial is the marketing name for Lincoln Financial Corporation and its affiliates including The Lincoln National Life Insurance Company, Fort Wayne, IN, and Lincoln Life & Annuity Company of New York, Syracuse, NY. Lincoln Financial affiliates, their distributors, and their respective employees, representatives and/or insurance agents do not provide tax, accounting or legal advice.
Lincoln is committed to creating an inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Follow us on Facebook, X, LinkedIn, Instagram, and YouTube. For the latest company news, visit our newsroom.
Be Aware of Fraudulent Recruiting Activities
If you are interested in a career at Lincoln, we encourage you to review our current openings and apply on our website. Lincoln values the privacy and security of every applicant and urges all applicants to diligently protect their sensitive personal information from scams targeting job seekers. These scams can take many forms including fake employment applications, bogus interviews and falsified offer letters.
Lincoln will not ask applicants to provide their social security numbers, date of birth, bank account information or other sensitive information in job applications. Additionally, our recruiters do not communicate with applicants through free e-mail accounts (Gmail, Yahoo, Hotmail) or conduct interviews utilizing video chat rooms. We will never ask applicants to provide payment during the hiring process or extend an offer without conducting a phone, live video or in-person interview. Please contact Lincoln's fraud team at [email protected] if you encounter a recruiter or see a job opportunity that seems suspicious.
Additional Information
This position may be subject to Lincoln’s Political Contribution Policy. An offer of employment may be contingent upon disclosing to Lincoln the details of certain political contributions. Lincoln may decline to extend an offer or terminate employment for this role if it determines political contributions made could have an adverse impact on Lincoln’s current or future business interests, misrepresentations were made, or for failure to fully disclose applicable political contributions and or fundraising activities.
Any unsolicited resumes or candidate profiles submitted through our web site or to personal e-mail accounts of employees of Lincoln Financial are considered property of Lincoln Financial and are not subject to payment of agency fees.
Lincoln Financial ("Lincoln" or "the Company") is an Equal Opportunity employer and, as such, is committed in policy and practice to recruit, hire, compensate, train and promote, in all job classifications, without regard to race, color, religion, sex, age, national origin or disability. Opportunities throughout Lincoln are available to employees and applicants are evaluated on the basis of job qualifications. If you are a person with a disability that impedes your ability to express your interest for a position through our online application process, or require TTY/TDD assistance, contact us by calling (866) 922-6543.
Salary Context
This $171K-$274K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $176K across 1540 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Lincoln Financial, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $212,000 based on 11,857 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($222K) sits 5% above the category median. Disclosed range: $171K to $274K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Lincoln Financial AI Hiring
Lincoln Financial has 8 open AI roles right now. They're hiring across AI/ML Engineer, Data Engineer, MLOps Engineer. Positions span Radnor, PA, US, Radnor, PA. Compensation range: $171K - $274K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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