About The Position

The Senior AI Product Manager shapes and leads the firm's most complex and strategically significant enterprise AI products and reusable AI capabilities across products, business domains, customer experiences, and enterprise workflows. The role treats AI as the product and owns strategy, discovery, prioritization, adoption, lifecycle management, and measurable outcomes, operating with significant autonomy to set product direction and ensure scalable AI solutions create measurable value. The role may cover strategic AI product or capability domains that enable AI creation and adoption; deliver AI-powered experiences; provide trusted information and intelligence; drive automation and decision support; or support governance, reliability, and operations. Products and services may include models, agents, skills, functions, tools, knowledge assets, retrieval capabilities, builder experiences, low-code solutions, platform capabilities, governance services, observability capabilities, and emerging AI technologies. The Senior AI Product Manager influences strategy across interconnected AI products, helps shape enterprise AI direction, and advises business, technology, product, risk, and operational leaders. The role partners across Engineering, Data, Product Management, Architecture, Experience, Risk, and Business areas to deliver customer and business value while ensuring capabilities are scalable, reusable, explainable, measurable, and aligned with responsible AI practices. It also strengthens AI Product Management through product leadership, coaching, mentoring, collaboration, and advancement of best practices.

Requirements

  • Bachelor's degree in a relevant technical, product, analytics, or business field, or equivalent professional experience.
  • Five or more years of Product Management experience, including ownership of complex technology, platform, data, digital, or AI products.
  • At least one year of experience with AI, machine learning, generative AI, agentic systems, intelligent automation, AI platforms, or advanced analytics.
  • Demonstrated success owning strategic products or reusable capabilities across multiple customers, teams, domains, products, or enterprise workflows.
  • Familiarity in at least one AI product specialty, with broad knowledge of enterprise AI technologies, data, platforms, governance, and architecture.
  • Product Management skills in strategy, discovery, experimentation, prioritization, roadmaps, analytics, adoption, and lifecycle management.
  • Ability to translate complex customer and business needs into product outcomes, technical requirements, evaluation criteria, and prioritized work.
  • Experience defining product success measures and evaluating tradeoffs across customer value, feasibility, cost, quality, performance, reuse, risk, and time to value.
  • Strong understanding of responsible AI, governance, privacy, security, compliance, model risk, monitoring, and enterprise controls.
  • Proven ability to influence leaders, lead cross-functional teams, coach others, and communicate complex topics clearly.

Nice To Haves

  • Master's degree in a relevant technical, product, or business field.
  • Experience leading enterprise AI products or reusable capabilities in financial services or another highly regulated industry.
  • Experience with low-code, no-code, and pro-code AI ecosystems, including Microsoft Copilot Studio, Power Platform, Azure AI, Databricks, or comparable technologies.
  • Experience defining AI evaluation, monitoring, observability, governance, security, privacy, model-risk, or regulatory controls.
  • Experience developing Product Management frameworks, organizational capabilities, communities of practice, or talent through coaching and mentoring.

Responsibilities

  • Set the vision, value proposition, outcomes, priorities, and roadmap for strategic AI products and capability domains.
  • Translate customer needs and business priorities into scalable AI product strategies, investment recommendations, product outcomes, requirements, evaluation criteria, and prioritized work.
  • Identify opportunities, dependencies, risks, overlaps, and tradeoffs across interconnected AI products and capabilities.
  • Own strategic AI products across the lifecycle, from discovery and launch through adoption, optimization, and retirement.
  • Define customers, use cases, value propositions, success measures, constraints, service expectations, and lifecycle plans.
  • Lead continuous discovery to identify customer problems, unmet needs, reusable patterns, and high-value AI opportunities.
  • Test product hypotheses through research, prototypes, experiments, evaluations, proofs of concept, and pilots; use customer evidence, product data, technical findings, and business measures to recommend whether to pursue, change, scale, pause, or stop an opportunity.
  • Define the product experience, including AI behavior, data and knowledge needs, integrations, human oversight, controls, monitoring, and support.
  • Partner with Engineering, Data, AI Science, Architecture, Cybersecurity, Experience, and Business teams to evaluate options, challenge assumptions, identify dependencies, and make informed tradeoffs.
  • Promote reusable, interoperable patterns across models, agents, skills, knowledge assets, workflows, platforms, and governance capabilities.
  • Recognize and address AI limitations and risks, including unreliable outputs, bias, data leakage, inappropriate actions, security threats, model drift, and workflow failure.
  • Define and monitor measures for customer value, business outcomes, adoption, reuse, quality, reliability, cost, operational performance, scalability, and risk.
  • Embed responsible AI, privacy, security, legal, regulatory, accessibility, records, and model-risk requirements throughout the product lifecycle; define intended uses, limitations, potential misuse or harm, data sensitivity, autonomy, access, human oversight, controls, and escalation paths.
  • Communicate product outcomes, health, risks, assumptions, dependencies, tradeoffs, and lessons learned to senior technical and nontechnical leaders and stakeholders, and serve as a trusted advisor on complex AI opportunities and decisions.
  • Influence leaders, lead cross-functional teams, coach others, and communicate complex topics clearly.

Benefits

  • Medical and prescription drug coverage
  • Dental insurance
  • Vision insurance
  • Voluntary benefits, such as accident, hospital indemnity, and critical illness coverage
  • Short- and long-term disability coverage at no cost to associates
  • Basic life and basic AD&D coverage at no cost to associates
  • 401k retirement plan
  • Health savings account
  • Flexible spending account
  • Ten paid holidays
  • 15 days of vacation for new associates beginning on January 1 of each year
  • Sick time
  • Personal days
  • Paid day for volunteerism
  • Associates may be eligible for bonuses and profit sharing
  • Employee Assistance Program
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