This is an exciting opportunity to own the technology product roadmap for Voya's advisor experience - partnering with the field to identify the problems worth solving, then delivering the AI-native tools that expand advisor capacity and improve client outcomes. ABOUT THE ROLE Voya Financial is hiring an Assistant Vice President of Product Management for the Advisor Experience. This role sits in the Digital & Wealth Management Technology organization: you partner with the Wealth Management business and the advisor field to understand and prioritize the business problems worth solving, then own the technology product roadmap and the digital solutions that address them - across the RAD and Investor Channel advisor copilot, meeting preparation, client context, proposal generation (WealthPath), next-best-action, and book management. This is a product leadership role one level below VP, and you lead a small team of product managers executing against that roadmap. You work within the product strategy set by the VP of Digital Product for Wealth Management, but you own the technology roadmap, discovery, specifications, and outcomes for the advisor experience. The operating model is deliberate: the business owns its strategy and results and advisors own the client relationship; you partner with them to frame the problem, and you own the technology solution that solves it. This is a deeply hands-on role: you write specs engineers actually use, evaluate AI prototype quality directly, make real-time trade-off calls, and partner daily with engineering. You are accountable for whether shipped products change advisor behavior, expand capacity, and improve client outcomes. This role reports to the VP of Digital Product for Wealth Management. Peer benchmarks: Senior/Principal Product Manager, Advisor Platform at Fidelity, Schwab, or LPL; Product Lead, Advisor Tools at a wealth-focused fintech. WHAT YOU'LL DO Own the Advisor Experience Technology Product Roadmap • Define and maintain a 12-18 month technology product roadmap across the advisor copilot, proposal generation, client context, and next-best-action - with clear prioritization rationale and measurable milestones. • Prioritize using advisor workflow research, adoption and usage data, field feedback, and competitive analysis; build the business cases that support investment decisions. • Define outcome-oriented success metrics - advisor capacity and time saved, proposal cycle time, active adoption, advisor satisfaction, and downstream client funding and conversion - and own accountability for those numbers post-launch. Partner With the Business to Identify Problems & Shape Solutions • Partner with Wealth Management leadership, advisors (RAD and Investor Channel), field operations, and distribution to identify, frame, and prioritize the business problems worth solving, bringing engineering and AI feasibility into the conversation so the problem definition and the technology response are shaped together. • Lead structured discovery with advisors - including direct observation of how they actually work - translating advisor workflow problems into crisp product specs and the technology solutions that address them. • Write PRDs and technical specifications a small AI engineering team can execute against; define acceptance criteria that account for model quality thresholds, latency targets, and suitability and fiduciary output constraints. • Maintain working fluency in the advisor workflow: prospecting, meeting preparation, proposal and portfolio construction, ongoing service, and book management - well enough to identify where AI changes outcomes at each stage. Drive AI-Native Advisor Tools • Own the product direction for the advisor copilot - meeting preparation, cross-channel client context, proposal drafting, and next-best-action - and evaluate RAG pipeline and agent behavior quality directly in staging. • Drive rapid prototype cycles - a working demo in days, not sprints - and use working software to earn advisor and stakeholder trust faster than slide decks. • Ensure AI outputs are structured to support - not replace - advisor judgment, with human-in-the-loop where appropriate, consistent with suitability obligations and the 2026 interagency model risk management guidance. Deliver With Engineering & Partners • Partner daily with AI engineers; make real-time trade-off calls throughout the build cycle. • Coordinate product launches with Compliance, Legal, Supervision, field enablement, and operations; own go-to-market: advisor training, rollout sequencing, and adoption measurement. • Partner with the rollover and Retirement-to-Wealth product owners so advisor tools actively support capture at the job-change moment. Lead & Develop • Lead a small team of product managers or a defined workstream; coach junior PMs and help raise the team hiring bar. • Build trusted relationships across Wealth Management, distribution, Compliance, and Supervision - influencing VP-and-above stakeholders across business units. • Identify compliance and supervisory risk exposure before it becomes an escalation. EDUCATION Bachelor's degree in Computer Science, Engineering, Finance, Economics, Mathematics, or a related discipline required; MBA or Master's in a quantitative or business field preferred. Equivalent professional experience considered. EXPERIENCE • 10+ years of product management experience, with at least 4 years in AI/ML or digital product roles at a technology company, fintech, or financial services firm. • Demonstrated track record of shipping digital or AI-powered products to production - owning the lifecycle from discovery through measurable adoption. • Leadership experience: has led product managers or owned a product workstream and defined a roadmap for an area independently. • Prior ownership of products in a regulated environment (wealth, brokerage, or financial services); experience navigating compliance, supervision, and legal review as part of the standard product process. • Experience influencing VP-and-above stakeholders without direct authority. AI & TECHNICAL FLUENCY - REQUIRED • LLM product experience: shipped at least one production feature using large language models; understands prompt and system-prompt design, context window management, and structured output extraction. • Agentic AI product design: understands tool use and multi-step reasoning, and where agents fail and how those failures affect advisor use cases. • Model evaluation and metrics: can define evaluation frameworks and assess whether an eval suite covers the right failure modes for an advisor context. • Data fluency: comfortable interrogating SQL and forming hypotheses from advisor usage and behavioral data; uses AI coding and agentic tools daily. • Experimentation: A/B test design, cohort analysis, and shadow-deployment patterns for AI features in production. ADVISOR & WEALTH DOMAIN - REQUIRED • The advisor workflow and book-of-business management: how advisors prospect, prepare, propose, transact, and service clients across a book. • Advisory models and the retail advice and brokerage ecosystem: UMA/SMA and managed accounts, proposal and portfolio construction, and custody/clearing and platform providers (e.g., Pershing, Schwab, Envestnet, Apex). • Suitability and conduct standards that shape advisor tools: Reg BI, fiduciary considerations, and how AI-generated recommendations must be governed. • FINRA supervision and communications-review requirements (books and records, correspondence supervision) and how they constrain advisor-facing AI features. • How advisor productivity tools drive capacity and support rollover capture and client funding. LICENSING / REGULATORY REQUIREMENT FINRA Securities Industry Essentials (SIE) required, or will need to be obtained early on in employment. Series 7 a plus given the advisor-facing nature of the role. PREFERRED QUALIFICATIONS • Direct experience building advisor-platform or advisor-productivity products at a broker-dealer, RIA platform, asset manager, or wealth-focused fintech. • CFP, CFA (or candidate), CIMA, or equivalent credentials. • History of building 0→1 AI products in an innovation lab or startup-within-a-large-institution context. • Hands-on experience with MCP (Model Context Protocol) integrations or multi-agent product design. • PMP, SAFe, or equivalent certification; voice-of-advisor research at scale (field studies, in-product feedback loops, adoption cohort analysis). #LI-LW1 Compensation Pay Disclosure: Voya is committed to pay that's fair and equitable, which means comparable pay for comparable roles and responsibilities. The below annual base salary range reflects the expected hiring range(s) for this position in the location(s) listed. In addition to base salary, Voya offers incentive opportunities (i.e., annual cash incentives, sales incentives, and/or long-term incentives) based on the role to reward the achievement of annual performance objectives. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Voya Financial is willing to pay at the time of this posting. Actual compensation offered may vary from the posted salary range based upon the candidate's geographic location, work experience, education, licensure requirements and/or skill level and will be finalized at the time of offer. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. $171,300 - $214,120 USD Be Well. Stay Well. Voya provides the resources that can make a difference in your lives. To us, this means thriving physically, financially, socially and emotionally. 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What We Offer • Health, dental, vision and life insurance plans • 401(k) Savings plan - with generous company matching contributions (up to 6%) • Voya Retirement Plan - employer paid cash balance retirement plan (4%) • Tuition reimbursement up to $5,250/year • Paid time off - including 20 days paid time off, nine paid company holidays and a flexible Diversity Celebration Day. • Paid volunteer time - 40 hours per calendar year Learn more about Voya benefits (download PDF) Critical Skills At Voya, we have identified the following critical skills which are key to success in our culture: • Customer Focused: Passionate drive to delight our customers and offer unique solutions that deliver on their expectations. • Critical Thinking: Thoughtful process of analyzing data and problem solving data to reach a well-reasoned solution. • Team Mentality: Partnering effectively to drive our culture and execute on our common goals. • Business Acumen: Appreciation and understanding of the financial services industry in order to make sound business decisions. • Learning Agility: Openness to new ways of thinking and acquiring new skills to retain a competitive advantage. 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