Senior AI Product Manager

Xylem•Charlotte, NC

4d•$165,000 - $180,000

About The Position

The Senior AI Product Manager leads product strategy, roadmap, and delivery for foundational AI platform solutions, including xylem.ai, Xylem’s secure internal platform for generative and enterprise AI capabilities. The role translates enterprise AI strategy into reusable, governed, scalable platform capabilities that accelerate adoption, reduce duplicative work, improve productivity, and enable responsible AI use across Xylem. The position partners with AI leadership, IT, Enterprise Architecture, Cybersecurity, Data Governance, Legal, Procurement, business stakeholders, and development teams to prioritize high-value capabilities, make platform decisions, and deliver secure, reusable AI products and services. The successful candidate combines product management discipline, technical depth, enterprise platform experience, and business acumen, engaging with engineers and architects and contributing to prototyping, solution design, or architecture decisions when needed. The role calls for senior product management experience and typically 10–15 years of relevant experience across product management, enterprise platforms, software engineering, AI/ML, data, digital transformation, or related technical leadership roles. A bachelor’s degree in a related field is preferred; an advanced degree is preferred but not required, and equivalent combinations of education and experience may be considered. The salary range is $165,000 to $180,000 plus bonus. Starting pay depends on factors including skills, experience, and work location.

Requirements

Typically 10–15 years of relevant experience across product management, enterprise platforms, software engineering, AI/ML, data, digital transformation, or related technical leadership roles.
Senior product management experience for enterprise platforms, AI/ML platforms, data platforms, SaaS products, or internal technology platforms.
Demonstrated ownership of roadmaps, prioritization, backlog management, product requirements, release planning, adoption, and value realization.
Technical depth to partner with engineers and architects and contribute to design, prototyping, architecture, and implementation tradeoffs.
Experience delivering AI, generative AI, automation, or data-enabled products from concept through scalable deployment.
Working knowledge of LLMs, RAG, AI agents, AI workflows, prompt orchestration, evaluation, telemetry, observability, APIs, cloud platforms, identity/access, and secure software practices.
Experience applying governance, privacy, security, compliance, responsible AI, and risk-management requirements to product and platform decisions.
Strong business acumen and ability to connect platform investments to business outcomes and measurable value.
Strategic thinking and ability to translate enterprise AI priorities into product decisions and execution plans.
Strong prioritization, product judgment, and scope discipline.
Ability to translate technical concepts into business decisions and business needs into actionable requirements.
Strong communication, stakeholder influence, and cross-functional leadership skills across technical teams, business teams, governance bodies, and senior leaders.
Passion for responsible innovation, ethical AI, user-centered product development, and enterprise change leadership.

Nice To Haves

Experience operating in complex, global, matrixed, or regulated environments.
Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, Product Management, Business, or a related field.
Advanced degree.

Responsibilities

Lead product strategy, roadmap, and delivery for foundational AI platform solutions, including xylem.ai.
Translate enterprise AI strategy into reusable, governed, scalable platform capabilities that accelerate adoption, reduce duplicative work, improve productivity, and support responsible AI use.
Partner with AI leadership, IT, Enterprise Architecture, Cybersecurity, Data Governance, Legal, Procurement, business stakeholders, and development teams to prioritize platform capabilities and make platform decisions.
Deliver secure, reusable AI products and services.
Own or contribute to product roadmaps, prioritization, backlog management, product requirements, release planning, adoption, and value realization.
Contribute to design, prototyping, architecture, and implementation tradeoffs when needed.
Connect platform investments to productivity, operational efficiency, customer impact, risk reduction, growth enablement, and measurable value.
Translate technical concepts into business decisions and business needs into actionable requirements.
Balance value, feasibility, risk, security, compliance, user experience, and delivery capacity in product decisions.