AI Technology Product Manager - Enterprise

Owns product strategy and delivery outcomes across The Baldwin Group's AI Engineering, Automation & Integration, and Cloud & DevOps portfolios, with primary focus on AI. This is a product management role: the person in this seat defines what gets built and why, sequences the roadmap across these domains against business value, and stays close enough to execution to keep initiatives on scope and on track — without losing ownership of the underlying product decisions.

Core Responsibilities

• Define and prioritize the AI product roadmap in partnership with business product owners, sequencing initiatives by business value, risk, and dependencies
• Translate business requirements into well-structured product requirements and backlog items for the engineering team
• Own outcomes across the AI portfolio: keep initiatives aligned to scope and value, and make the prioritization calls when trade-offs arise
• Direct AI, automation/integration, and cloud vendors and implementation partners, holding them accountable to product requirements and milestones
• Lead cross-functional rollout planning and stakeholder alignment for AI solutions going into production
• Own risk visibility across the portfolio — surface and resolve issues that threaten product outcomes, escalating proactively
• Own product outcomes for Automation & Integration initiatives (workflow automation, iPaaS, system integrations), balancing platform consolidation, reliability, and business enablement
• Own product outcomes for Cloud & DevOps initiatives (infrastructure platforms, CI/CD, developer tooling), partnering with engineering leads on roadmap sequencing and value delivery

Product Strategy & Discovery

• Define and continuously refine vision, strategy, and measurable objectives for AI initiatives, ensuring clear alignment with Baldwin's brokerage strategy and operating model
• Develop and maintain an outcome-oriented roadmap that balances regulatory, operational, user experience, and technical considerations; socialize and adjust based on evidence and stakeholder input
• Lead structured discovery (stakeholder interviews, journey mapping, qualitative research, workshops) to understand user problems and opportunities for AI-driven solutions
• Partner with Analytics and business teams to translate behavioral data, incident trends, and operational metrics into actionable product insights and hypotheses
• Translate problems and opportunities into well-formed epics, features, and user stories with clear acceptance criteria for Agile delivery teams

Product Ownership & Execution

• Own the AI Engineering, Automation & Integration, and Cloud & DevOps backlogs: prioritize based on customer impact, risk, regulatory needs, dependencies, and capacity, using recognized frameworks (e.g., RICE, WSJF, value vs. effort)
• Act as product lead within Agile ceremonies (planning, backlog refinement, reviews), ensuring work items are ready, understood, and anchored to defined outcomes
• Oversee functional validation for key features: define test scenarios, support test case design, review results, and accept/reject work against acceptance criteria
• Define and track product KPIs and success metrics (adoption, task completion, error/incident rates, cycle times, NPS/CSAT); run and interpret small experiments (A/B tests, pilot cohorts) to guide iteration
• Serve as primary point of contact for designated business areas on AI, automation/integration, and cloud/DevOps initiatives, managing expectations and aligning on priorities and trade-offs
• Facilitate cross-functional decision making, presenting clear options, impacts, and recommendations to leaders and governance forums
• Support change adoption by partnering with Training, Communications, and local leaders to embed new AI capabilities into processes and roles
• Provide peer coaching and informal mentoring to Associate and Technology Product Analysts on discovery methods, story writing, prioritization, and stakeholder engagement

Required Knowledge, Skills & Abilities

• Advanced understanding of end-to-end product lifecycle management, from discovery and definition through delivery, measurement, and iteration
• Ability to articulate and maintain a clear product vision and strategy, tying decisions to business outcomes, operational efficiency, client value, and risk management
• Strong skills in qualitative and quantitative discovery: framing problems, conducting interviews/workshops, synthesizing insights, and translating findings into hypotheses and requirements
• Proficiency in writing high-quality epics, features, and user stories, including non-functional requirements, that support itera