AI Product Owner, Intelligent Operations

Responsibilities

Own the Intelligent Operations AI roadmap

· Define and maintain the product vision and roadmap for AI across enterprise systems, including Operations, Finance, and HR applications, aligned to business and AI strategy.

· Identify, prioritize, and sequence high-impact AI/automation use cases across supply chain, inventory, finance, accounting, and people processes.

· Manage the product lifecycle end to end — from opportunity framing through delivery, adoption, and measured outcomes — with tight feedback loops.

· Turn fragmented tools, data, and processes into cohesive, secure, and reliable AI solutions.

Partner cross-functionally with Operations, Finance, Accounting, HR, and People Development

· Act as the central product partner for these teams — assessing needs, defining requirements, and establishing success measures for AI initiatives.

· Redesign and transform business processes around agent-driven automation — not just bolting AI onto legacy workflows.

· Enable AI-driven capabilities across our enterprise stack: intelligent automation, predictive analytics, copilots and agents, anomaly detection, and AI-assisted workflows (e.g., invoice automation, demand forecasting, inventory optimization, recruitment, onboarding, finance close).

· Translate business and functional requirements into clear product requirements, specs, and acceptance criteria that engineering, data science, and IT can deliver against.

Drive delivery, adoption, and measurable value

· Design and lead pilots and structured experiments with clear hypotheses, rollout criteria, and measurable outcomes.

· Own backlog, roadmap, priorities, and communication of progress and outcomes to stakeholders up to executive level.

· Drive adoption: enablement, training, SOP updates, usage metrics, and continuous improvement from feedback.

· Build ROI cases, track realized value, and justify AI investments.

Operate within governance and partner with technical teams

· Work hands-on with enterprise platforms (e.g., ERP, finance, planning, OMS) and their integrations to ground AI solutions in real data, controls, and operational ownership.

· Operate within AI governance, data, security, privacy, and compliance standards; manage risks and escalate blockers early.

· Partner with engineering, data science, IT, security, and external vendors to evaluate solutions and determine paths to market

Requirements

We value demonstrated impact and a builder mindset over any specific number of years — but this role requires real depth.

Required

· 5–10 years of relevant experience, with at least 5 years in product management or product ownership owning roadmap, requirements, and delivery.

· Hands-on experience delivering AI, automation, or digital transformation initiatives across enterprise functions — ideally spanning more than one of Operations, Finance, or HR.

· Strong process orientation: ability to map end-to-end processes, spot automation-ready opportunities, and drive transformation, not just deliver software.

· Familiarity with AI/ML and GenAI (agents/copilots, RAG, LLM integration, intelligent automation) and how they reshape process design.

· Ability to write clear, detailed requirements and translate between business stakeholders (Ops, Finance, HR) and technical teams (engineering, data, IT).

· Experience leading complex, cross-functional programs and influencing stakeholders up to executive level without authority.

· Analytical and outcomes-driven: comfortable building ROI cases, running experiments, and measuring adoption and value.

· A builder mindset — you move fast, are comfortable deciding with ~70% of the data, and love shipping.




Preferred

· Background in supply chain, inventory, finance, or enterprise apps (ERP, HCM, finance, planning, CRM platforms and their modules).

· Direct experience owning AI roadmaps for Operations, Finance, or HR systems in-house or at a platform/consultancy.

· Experience with enterprise systems (e.g., SAP, Oracle, Workday, NetSuite, Salesforce, Anaplan) and integrating AI/automation into them (APIs, middleware, RPA).

· Experience with AI agents and automation platforms (e.g., Copilot Studio, agent platforms, UiPath/Power Automate-style RPA).

· Background in beauty, retail, consumer goods, or another high-velocity operations environment.

· Familiarity with AI governance, data quality, and compliance in regulated/enterprise contexts