Sr. Product Manager - Tech, OpsTech Solutions, Delivery Software Engineering (DSE)

Every Amazon package that ships, every grocery order that is fulfilled, and every locker that opens depends on technology our teams keep running. Amazon's OpsTech Solutions (OTS) is the IT operations and infrastructure organization for all of Amazon Worldwide Operations including Worldwide Grocery Stores (WWGS), delivering reliable technology to more than one million associates and operators across every geography and all business miles. OTS is transforming from reactive support to proactive, AI-powered service delivery. The data products powering that transformation are at the center of how the organization plans, decides, and operates.

What this role is: You will own the product strategy for the OTS Data Products portfolio, spanning four data products (Nodal Efficiency, Timesheet Adherence, Scenario Planner, and Short Term Planning) and five agentic workflow products (Printer Agent, MCM Agent, CSDA, OTS MCP, and OneVoice). You decide what gets built, what gets deprecated, and how these products become one coherent, reusable portfolio. This is the role that determines whether OTS's data investments compound or stay siloed.

This is a platform and portfolio role. You will work across two engineering organizations, ANCHOR and Delivery Software Engineering (DSE), as well as partner analytics and program teams. An emerging ecosystem of AI agents and Model Context Protocol (MCP) services is an important part of the landscape, but your scope is the wider OTS data products estate, not any single team or service. You will define and drive the shared product strategy, standards, and access layer that these teams build on and that OTS customers consume.

Across OTS, teams have built valuable data products (forecasting services, operational metrics grounded in validated data), each proven in its own domain. The opportunity is to connect these strong point solutions across third-party platforms (ServiceNow) and in-house 1P services into one coherent portfolio, so that every new data-driven solution becomes a matter of configuration and connection rather than a net-new build. Your customers span field technicians who consume operational intelligence, program managers who configure forecasts and derive AI-driven insights, leaders who query validated metrics in natural language, and engineers who integrate with data products programmatically.

Key Highlights

• Own the product strategy and roadmap for the OTS Data Products portfolio (forecasting, science, analytics, and data tooling) across ANCHOR and Delivery Software Engineering (DSE) teams.
• Drive the reactive-to-proactive transformation by making OTS data accessible, reusable, and trustworthy through a foundational-services model: design once, deploy many.
• Shape the AI agent and MCP access layer that lets operators and leaders reach OTS data through natural-language and programmatic interfaces.
• Set the direction that multiple engineering teams build toward, backed by executive sponsorship and a clear mandate across the portfolio.
• Serve diverse customer personas across a spectrum of data latencies, from near-real-time operational needs on the front line to executive-level strategic insights.

Key job responsibilities

• Define and own a multi-year product vision and roadmap for OTS data products, unifying forecasting, science, analytics, and the AI agent and MCP ecosystem into one coherent portfolio.
• Act as the voice of the customer across OTS program teams, translating operational needs into product requirements and making disciplined trade-offs between time, effort, and feature depth.
• Partner with engineering leaders across contributing teams to shape architecture decisions, resolve overlap between services (e.g., ensuring a knowledge graph calls an existing metrics service rather than duplicating it), and drive build-vs-buy-vs-reuse decisions.
• Drive the AI agent and MCP access-layer strategy, establishing clear ownership boundaries between the common front door and supporting data services.
• Establish north-star and adoption metrics that make the foundational-services thesis measurable, and own the Monthly and Quarterly Business Review reporting standards that keep the portfolio accountable.
• Align partner engineering teams and stakeholders across competing priorities - driving adoption so teams choose to build on the shared portfolio rather than around it.
• Contribute to annual planning mechanisms (OP1/OP2) with clear, well-reasoned investment proposals, and maintain mechanisms to continuously capture voice of the customer from both internal OTS employees and operational customers.

A day in the life

Your day moves between strategy and execution. You review portfolio metrics, update roadmaps with the contributing teams, run voice-of-the-customer sessions to make sure priorities reflect real operational pain points across personas, from a field technician relying on operational intelligence to a leader asking a natural-language question of validated metrics. You join architecture discussions to resolve how forecasting, the MCP and agent layer, supporting data services fit together, and where boundaries between overlapping services should sit. In the afternoon, you make prioritization trade-offs with engineering leaders across teams whose roadmaps you influence but do not control, then shift to drafting strategy narratives and investment proposals for senior review.

About the team

OTS sits within Amazon's largest support organization for Worldwide Operations, building a broader strategy to enhance support operations through technology and AI. OTS data products are how that strategy becomes actionable: forecasting and science services that help program teams plan, operational metrics grounded in validated data, and an emerging AI agent and MCP ecosystem that meets users at the point of need. The ANCHOR team is a key contributor to this landscape, delivering products such as OPAL and agentic tooling, and it partners with Delivery Software Engineering (DSE), Global Workforce Management (GWM), and the OTS and RME program teams. This role defines what the OTS data products portfolio should be across those teams; the engineering organizations deliver the how.