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

As a 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 verbal communication, documentation, analytical thinking, and sound judgment. - Proven ability to influence and lead through others, manage cross-functional teams, and navigate conflict. Preferred Qualifications, Capabilities, and Skills: - Asset Management or financial services experience, and/or experience delivering solutions for a Client Service organization. - Experience delivering AI/ML, generative AI, or conversational AI products—ideally in client servicing, contact center, or customer inquiry contexts. - Familiarity with the modern AI stack—LLM platforms, vector databases, RAG pipelines, MLOps/LLMOps, and AI evaluation and observability tooling. - Experience partnering with UX research and design to improve client journeys; familiarity with knowledge management or client lifecycle operations. - AI-driven mindset and a passion for using AI copilots to raise product decisioning, documentation quality, and delivery velocity.