Role Summary:

As a Technical Product Manager specializing in AI Solutions, this role will own the generative AI and automation product portfolio for Customer Operations at Cencora — both the systems our customers use directly and the systems our employees rely on when supporting them. You will serve as the product owner for a dedicated engineering team, driving a roadmap that spans AI-powered self-service, AI assistance for customer-facing support personnel, and increasingly automated resolution workflows.

This is a hands-on product role. You will lead discovery with service and platform teams, define assistant and agent behaviors, manage prompt and context engineering as a production discipline, build the evaluation frameworks that determine whether AI features are ready to ship, and iterate on live capabilities based on real-world performance. We're looking for someone who has built and shipped with this technology — not someone who has managed it from a distance.

The successful candidate combines customer operations domain knowledge with practical experience shipping LLM-enabled products. Direct experience implementing LLM-enabled automation workflows, agentic AI, or custom generative AI solutions — ideally in a customer service context — is required.

This role resides within our Global Data and Technology Services organization (GDATS) as part of the Data, Analytics and AI domain at Cencora.

Primary Duties and Responsibilities:

• Own the product vision, roadmap, and backlog for AI in Customer Operations, acting as the product owner for an engineering team within our scaled agile planning cadence.

• Lead product discovery with customer service and digital platform stakeholders to identify, prioritize, and validate high-value AI use cases, with defined success metrics (e.g., containment/deflection, FCR, AHT, CSAT, adoption, response quality).

• Develop detailed product requirements documents (PRDs), user stories, and functional specifications for AI-driven capabilities — including assistant and agent behaviors, conversation and escalation flows, knowledge grounding and retrieval strategy, and guardrails.

• Create, test, iterate, and publish production-ready prompts and agent configurations for customer operations use cases, treating prompt and context engineering as an ongoing discipline rather than a one-time setup.

• Own AI quality end to end: define evaluation frameworks (test datasets, automated evaluation, human review), set launch quality bars, monitor production behavior, and drive continuous improvement.

• Advise and consult stakeholders on build vs. buy vs. configure decisions across our enterprise AI platform landscape, using a strategic, data-driven approach.

• Manage product development cycles with internal engineering and external vendor resources; oversee test planning, system integration testing, validation of results, and issue resolution.

• Partner with legal, compliance, privacy, and security stakeholders to deliver AI capabilities responsibly in a regulated healthcare environment.

• Work closely with end users to drive adoption, including training, enablement, feedback loops, and support for AI tool usage.

Experience and Educational Requirements:

• Bachelor's degree in Computer Science, Information Systems, Business, or a related field.

• 6+ years of relevant product management or related work experience.

• Demonstrated experience defining, deploying, and iterating on AI enabled solutions and automations in an enterprise or B2B/B2C product environment.

Required AI Experience:

• Candidates should be able to speak concretely about AI products they have built and shipped.

• Experience implementing LLM-enabled automation workflows, agentic AI, or custom generative AI solutions in production — ideally for customer service or customer experience use cases. Examples include AI assistants or copilots for service agents, customer-facing conversational AI, intelligent triage and routing, and automated case resolution.

• Working familiarity with the modern generative AI stack: LLM APIs (Azure OpenAI, Anthropic, or comparable), retrieval-augmented generation and knowledge grounding, function/tool calling, and agent orchestration frameworks or platforms (e.g., LangChain/LangGraph, Semantic Kernel, Microsoft Copilot Studio, Salesforce Agentforce, or similar).

• Hands-on prompt engineering experience, including creating, testing, versioning, and optimizing prompts and conversational flows for customer-facing applications.

• Experience evaluating and monitoring AI quality — evaluation datasets, automated or LLM-assisted evals, human review processes, and hallucination/safety monitoring — and using those signals to inform release decisions.

• A current, working understanding of LLM capabilities and tradeoffs (quality, latency, cost, safety) and a commitment to staying current in a fast-moving space.

Required Domain Expertise:

• 3+ years of product management experience in customer service, CX technology, enterprise e-commerce, or customer platform domains.

• Strong understanding of customer service operations, including contact center technologies, case management, and service metrics (CSAT, NPS, FCR, AHT).

• Familiarity with enterprise CRM platforms; Salesforce strongly preferred.

• Proven experience with customer-facing digital platforms and portals in B2B environments.

• Track record of improving customer satisfaction and operational efficiency through technology initiatives.

Minimum Skills, Knowledge, and Ability Requirements:

• Ability to operate independently as the product owner for a team — scoping ambiguous problems, making decisions, and owning outcomes.

• Strong leadership and collaboration skills within cross-functional teams, with excellent verbal and written communication.

• Sufficient technical depth to engage engineers on architecture and design tradeoffs for AI systems (APIs, integration patterns, data flows) without needing to write the code yourself.

• Strong problem-solving and analytical skills, with rigor around measurement and experimentation.

• Comfort operating in a regulated healthcare environment with compliance, privacy, and responsible AI considerations.

Who Thrives in This Role

You are likely a strong fit if:

• You have shipped at least one LLM-powered capability to real users and can walk through the architecture, how you evaluated it, and what you learned along the way.

• You can sketch out an agentic customer service workflow — retrieval, tool calls, escalation logic, guardrails — and talk through the tradeoffs involved.

• You follow AI developments closely and are motivated by applying new capabilities to real, high-volume customer problems.

• You want ownership: a dedicated engineering team, a funded roadmap, and accountability for outcomes.

This is probably not the right fit if:

• Your AI experience is primarily as an end user of tools like ChatGPT or Copilot, or limited to pilots and demos that didn't reach production.

• You have overseen AI initiatives at arm's length (program or vendor management) without direct product ownership of the AI capability itself.

• You prefer executing against fully defined requirements over working through ambiguous, early-stage product spaces.

We provide compensation, benefits, and resources that enable a highly inclusive culture and support our team members’ ability to live with purpose every day. In addition to traditional offerings like medical, dental, and vision care, we also provide a comprehensive suite of benefits that focus on the physical, emotional, financial, and social aspects of wellness. This encompasses support for working families, which may include backup dependent care, adoption assistance, infertility coverage, family building support, behavioral health solutions, paid parental leave, and paid caregiver leave. To encourage your personal growth, we also offer a variety of training programs, professional development resources, and opportunities to participate in mentorship programs, employee resource groups, volunteer activities, and much more. For details, visit