Vice President, Product Manager - Asset Management Client Service Experience - Service Assist

As Service Assist Product Manager, you will bring strong product discipline and a data-driven, AI-first mindset-spanning generative AI, machine learning, and natural language processing (NLP)-to lead strategy and end-to-end execution across business and technology teams, mobilizing partners to deliver measurable client, operational, and risk outcomes.

Job Responsibilities:



* Define and maintain the Service Assist product vision, strategy, and roadmap, aligned to business priorities, client experience goals, and the firm's AI ambitions.



* Champion an AI-first approach, identifying and prioritizing high-value use cases for generative AI, machine learning, and intelligent automation-such as intelligent intake and routing, conversational AI and virtual assistants, response generation, summarization, and retrieval-augmented generation (RAG).



* Lead transformation and change management, driving user adoption and operational readiness across servicing teams.



* Partner with cross-functional triad teams-Engineering, Design, and Data Science, alongside Service operations and Risk & Controls-to ensure alignment, clear ownership, and successful delivery.



* Run an agile governance and delivery cadence, and own and prioritize the product backlog, balancing scope, timelines, dependencies, and risk.



* Define OKRs and success metrics-response time, accuracy and quality, automation and deflection rates, risk reduction, and client satisfaction (CSAT)-and use experimentation and A/B testing to drive continuous improvement.



* Establish AI evaluation frameworks, guardrails, and monitoring-covering model accuracy, hallucination and bias mitigation, explainability, and responsible-AI compliance.



* Translate complex AI, data, and technology concepts into clear narratives for senior and non-technical audiences, proactively managing stakeholders and driving timely decisions and escalations.

Required Qualifications, Capabilities, and Skills:



* Proven, hands-on product management experience with agile practices-roadmaps, backlogs, prioritization, and iterative delivery.



* Strong conceptual command of AI/ML, generative AI, and large language models (LLMs)-including prompt engineering, retrieval-augmented generation (RAG), and agentic AI-and the ability to translate them into product features such as automation, summarization, intent classification, and intelligent routing.



* High data literacy, with the ability to interpret data, define metrics, and draw sound conclusions across quality, cycle-time, and adoption measures.



* Ability to use AI-assisted and no-code/low-code tooling to independently produce data-science-style outputs-queries, analyses, experiments, and prototypes-without deep hands-on coding.



* Working knowledge of responsible AI, model evaluation, and AI governance, partnering with Data Science and Engineering on model performance and safe deployment.



* Excellent written and...