Senior Product Owner

Position: Senior Product Owner

Location: Fort Mill, SC

Employment Type: Full-Time

Experience: 8–10+ years

Position Overview: Incedo is seeking an experienced Senior Product Owner to support the development and evolution of an AI-powered advisor platform within the wealth management industry. This individual will work at the intersection of product management, financial services, and artificial intelligence, translating business objectives and advisor needs into actionable product requirements that drive meaningful business outcomes. The ideal candidate brings 8–10+ years of experience supporting wealth management, financial advisory, investment, or related financial services platforms, along with exposure to artificial intelligence, generative AI, AI-enabled workflows, or intelligent automation. This role requires a hands-on product owner who can translate complex business problems into clear user stories, manage and prioritize product backlogs, coordinate cross-functional delivery teams, and ensure AI-enabled capabilities are intuitive, reliable, secure, and aligned with business and regulatory requirements.

Key Responsibilities: Product Ownership & Strategy: Partner with business stakeholders, product leadership, technology teams, and subject matter experts to define product priorities, establish a roadmap, and deliver AI-powered capabilities aligned with business objectives. Requirements & Backlog Management: Translate business needs, advisor feedback, and strategic priorities into well-defined epics, features, user stories, acceptance criteria, and actionable development requirements. Wealth Management, Investments or Financial Services Domain Expertise: Apply knowledge of financial advisory workflows, investment platforms, advisor technology, financial planning, client servicing, and practice management to identify opportunities for improving advisor productivity and client experiences. AI Product Enablement: Support the development and implementation of AI-enabled product capabilities, including conversational AI, intelligent assistants, contextual information retrieval, workflow automation, AI-generated summaries, and decision-support tools. Advisor Workflow Optimization: Identify opportunities to simplify complex processes, reduce manual administrative work, surface relevant insights, and embed intelligent assistance into existing advisor workflows. Agile Delivery: Collaborate with engineering, UX/UI, QA, architecture, data, and AI teams to refine requirements, manage dependencies, participate in sprint planning and reviews, and ensure timely delivery of high-quality product increments. Stakeholder Management: Facilitate discussions across business and technology teams, resolve requirement ambiguities, communicate trade-offs, and maintain alignment on priorities, scope, and delivery expectations. AI Governance & Risk: Partner with compliance, information security, risk, and legal stakeholders to incorporate appropriate controls for data privacy, access management, traceability, human oversight, and responsible AI usage. Testing & Acceptance: Define acceptance criteria, support functional and user acceptance testing, validate business outcomes, and ensure delivered features meet established requirements and quality standards. Product Analytics & Continuous Improvement: Evaluate user feedback, adoption metrics, operational efficiency, and product performance to identify enhancements and inform future roadmap decisions. Release & Change Management: Support release planning, rollout readiness, stakeholder communications, and user enablement to drive adoption of new product capabilities. Required Qualifications8–10+ years of experience in product ownership, product management, business analysis, or a closely related role within financial services. Strong experience supporting wealth management, financial advisory, investment management, brokerage, or advisor-facing technology platforms. Demonstrated experience translating business needs into detailed, testable user stories, acceptance criteria, functional requirements, and prioritized product backlogs. Experience working in Agile/Scrum environments with cross-functional software engineering and delivery teams. Practical exposure to artificial intelligence in a product or business context, such as generative AI, conversational AI, AI assistants, intelligent automation, machine learning-enabled features, or AI-driven workflow solutions. Ability to bridge business and technical stakeholders, communicate complex concepts clearly, and drive requirements through implementation. Strong analytical, problem-solving, prioritization, and stakeholder management skills. Understanding of data privacy, information security, and risk considerations associated with financial services technology. Excellent written and verbal communication skills, with the ability to operate effectively in a fast-paced, collaborative environment.

Preferred Qualifications: Experience with AI-powered advisor assistants, enterprise copilots, agentic AI solutions, or AI-enabled enterprise applications. Familiarity with large language models (LLMs), retrieval-augmented generation (RAG), AI orchestration, prompt engineering, or enterprise knowledge retrieval. Experience integrating AI capabilities with existing enterprise platforms, APIs, data services, or business workflows. Exposure to financial planning, portfolio management, investment research, client relationship management (CRM), account servicing, or advisor practice management systems. Experience defining product success metrics, evaluating pilot results, and driving adoption of emerging technology capabilities. Familiarity with responsible AI principles, model output validation, explainability, human-in-the-loop controls, and AI governance practices.

What Success Looks Like: Product requirements are clear, actionable, testable, and aligned with business priorities. AI-enabled capabilities address meaningful advisor and business needs while integrating effectively into existing workflows. Cross-functional teams have clear priorities, dependencies, and acceptance criteria to support predictable delivery. Product enhancements improve advisor efficiency, access to relevant information, and overall user experience. AI capabilities are delivered with appropriate attention to security, governance, reliability, and human oversight. Product adoption, stakeholder satisfaction, and measurable business value improve over time.