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Senior Product Manager - Tech, AI Cost Governance, AWS Insights and Optimizations

Amazon.com Inc

  • Seattle, WA
  • 2 days ago

    Highlights

    You will partner with engineering leaders, applied science leaders, and product leaders across Bedrock, AgentCore, and the broader AWS generative AI portfolio to ensure cost governance is designed in rather than retrofitted, and you will drive alignment on strategy and investment across multiple organizations without owning the teams that execute it. This is the highest-ambiguity, highest-leverage product space in the organization: the mechanics of tokenomics, attribution, and control for generative AI workloads are still being defined across the industry, and the decisions made here set the direction that partner service teams, enterprise customers, and eventually all industry players respond to.

    Numbers & Facts

    LocationSeattle, WA
    IndustryRetail
    Company Size10,000 employees or more
    Year Founded1994
    Websitehttp://Amazon.com/militaryroles

    Description

    We"re building the future of cloud financial management, and the hardest unsolved problem in it is AI cost. Customers are moving from experimenting with generative AI to running it in production at scale. Spend is driven by tokens, model choice, inference patterns, and increasingly by agents that make their own consumption decisions. The AWS Billing organization processes millions of events per second to deliver the cost, usage, and optimization insights that power financial decisions at the world"s largest enterprises. We are now extending that foundation to give customers the ability to understand, allocate, control, and optimize AI spend with the same rigor they apply to compute and storage today.

    As Senior Product Manager, you will execute AWS"s strategy for AI cost governance. This is the highest-ambiguity, highest-leverage product space in the organization: the mechanics of tokenomics, attribution, and control for generative AI workloads are still being defined across the industry, and the decisions made here set the direction that partner service teams, enterprise customers, and eventually all industry players respond to. You will own the product bets that define the category.

    In this role, you will define what it means to govern AI spend on AWS: how cost is attributed at the token, model, and agent level; how customers allocate that cost to teams, applications, and business units; and how they set and enforce controls before spend, rather than explaining it afterward. You will write the strategy documents and PR/FAQs for the most consequential launches, run the customer conversations, and make the hard trade-off calls on scope, sequencing, and where AWS should lead versus follow. You will pressure-test metering, API, and interface designs directly with engineering, and dig into consumption data and customer telemetry to understand where the real cost drivers and governance gaps are. You will own the measurement of whether these capabilities actually change customer behavior, including adoption, spend under active governance, and the degree to which cost visibility unblocks AI expansion, and build the review mechanisms that hold the organization accountable to it.

    You will make the calls on how AI cost governance extends to emerging surfaces, including foundation model inference, agentic workloads, and third-party and marketplace model consumption, and on when AWS should build new primitives versus extend existing cost management constructs. You will partner with engineering leaders, applied science leaders, and product leaders across Bedrock, AgentCore, and the broader AWS generative AI portfolio to ensure cost governance is designed in rather than retrofitted, and you will drive alignment on strategy and investment across multiple organizations without owning the teams that execute it. You will represent this product area to senior AWS leadership, enterprise CFOs and FinOps practitioners, and industry analysts, and you will shape how the market thinks about the economics of running AI in production.

    This role requires deep technical judgment, comfort operating with incomplete information on problems that have no precedent, and the influence to move organizations you do not control. If you are excited about defining a product category that does not yet exist - and about the fact that every enterprise scaling generative AI will eventually need what you build - this role offers the opportunity to set AWS"s position on the economics of AI.

    Key job responsibilities

    • Engage with customers through a variety of channels and serve as the voice of the customer internally.
    • Gain feedback from customers to ensure right focus in building our products
    • Manage the entire product life cycle from strategic planning to tactical execution.
    • Partner with engineering teams to deliver on the product roadmap.
    • Establish goals and review metrics to identify opportunities and measure the success of the product features.
    • Provide effective written and verbal updates on the products and key projects to senior leadership and stakeholders.

    About Company

    At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

    Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

    It’s Always Day 1
    At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

    Our Leadership Principles
    Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

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