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 iterative delivery and clear testing
- Comfort owning outcomes across multiple concurrent initiatives — sequencing, trade-offs, and vendor accountability — without losing sight of the product strategy driving them
- Solid understanding of web/SaaS and AI/ML product concepts (e.g., integrations, APIs, model deployment considerations, roles/permissions, environments) sufficient to engage deeply with Engineering and make informed trade-off decisions
- Working knowledge of integration and automation platform concepts (iPaaS, workflow orchestration, API management) sufficient to evaluate trade-offs across integration platforms and low-code automation tools
- Working knowledge of cloud infrastructure and DevOps concepts (CI/CD, infrastructure as code, cloud governance) sufficient to engage with Cloud/DevOps engineering teams on roadmap sequencing and technical trade-offs
- Working knowledge of insurance brokerage concepts (client lifecycle, policy placement, renewals, servicing) and how they're represented in technology platforms, or demonstrated ability to develop this expertise quickly
- Strong facilitation and communication skills, with the ability to align diverse stakeholders, present options and trade-offs succinctly, and manage disagreement constructively
- Proven ability to lead cross-functional teams without direct authority, keeping work focused on outcomes and delivering on commitments
- Comfort operating in Agile environments and collaborating closely with Scrum Masters, Engineers, QA, and other partners
Qualifications
- Bachelor's degree in information systems, computer science, business, data/analytics, engineering, or a related field; or equivalent combination of education and experience
- 4–6 years of progressive experience in product management or technical product ownership, including direct ownership of roadmaps and backlogs for business applications or SaaS products
- Experience with AI/ML product or platform initiatives strongly preferred
- Experience with integration/automation platform (iPaaS, workflow automation) or cloud/DevOps platform initiatives preferred
- Direct experience with technology products in insurance, brokerage, or financial services, or in other highly regulated, B2B/B2B2C environments preferred
- Hands-on experience with Agile/Scrum and related toolsets (Jira or Azure DevOps for backlog management; Confluence/SharePoint for documentation) preferred
- Familiarity with product management frameworks from accredited programs (Cornell/eCornell, Pragmatic Institute, AIPMM, Product School, or similar) preferred
- Experience defining and tracking KPIs, running small experiments, and using data/analytics or BI tools to inform decisions preferred
- Relevant certifications (Pragmatic Institute, AIPMM, CSPO/PSPO, SAFe PO/PM, or university-backed product management certificates) are a plus
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