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Software Development Engineer , Project Dawn

Amazon.com Inc
  • Seattle, WA
    3 days ago

    Job Description

    Do you want to build software systems powered by generative AI that serve hundreds of millions of customers? The OAS Offers Tech organization owns the systems which make the world"s product catalog available on Amazon and ensure they are accurate, complete, and highly available to customers at scale. We are building the next generation of generative AI backed solutions to power critical customer facing shopping experiences across all Amazon surfaces, including the Amazon app, web, Alexa, Rufus, and beyond.

    As an SDE 2 on this team, you will independently design, deliver, and operate software features and systems that leverage state of the art deep learning and generative models across the full development lifecycle-from working backwards from customers through design, implementation, testing, deployment, and production operations. You will own technical decisions and make design trade-offs that balance short-term delivery with long-term maintainability, collaborating alongside a team of passionate engineers and scientists to solve problems like intelligent offer extraction, automated product listing enrichment, and AI powered selection tools that operate at internet scale. You will mentor other engineers on your team, coach others through code reviews and design discussions, and ensure that the software you produce can be maintained and extended by those not familiar with the code. You will bring clarity to difficult problems with visible risks or roadblocks, navigate ambiguous problem spaces with increasing independence, and drive operational excellence across the systems you own.

    This is a unique opportunity to build experiences used by hundreds of millions of people worldwide while tackling technical challenges at the intersection of large scale distributed systems and generative AI. If you are excited about shipping high impact, customer facing products, making meaningful design trade-offs at scale, and want to shape the future of how customers discover and purchase products on Amazon, we would love to hear from you.

    Key job responsibilities

    • Own end to end design, development, deployment, and operational health of services leveraging large language models and generative AI to power intelligent shopping experiences at scale.
    • Design and deliver distributed software features and systems powering production selection processing pipelines, from ingestion of the world"s product catalog through to making offers available for customers.
    • Develop deep expertise in Amazon"s catalog systems and drive their evolution to support next generation selection and offer processing.
    • Partner with applied scientists and senior engineers to process massive datasets, scale ML models, and define evaluation criteria. Take ownership of ambiguous integration challenges across teams.
    • Influence tech strategy around data enrichment pipelines, model optimization frameworks, and evaluation methodologies. Drive architecture decisions, articulating trade-offs and risks clearly.
    • Prototype new technologies and independently drive generative AI techniques from experimentation into production, navigating roadblocks and escalating risks appropriately.
    • Own operational excellence for your systems. Mentor teammates through code reviews, design discussions, and technical coaching.
    • Contribute to team level technical growth by sharing expertise in distributed systems and generative AI, and mentoring junior engineers.

    A day in the life

    You will spend most of your time designing and building distributed extraction pipelines that convert unstructured merchant website data into structured product offers using LLMs and browser automation. You will own production health of your services, maintaining offer freshness and accuracy SLAs. You will partner closely with Applied Scientists on model accuracy, the Selection Management team on data quality, and OAS Purchase Enablement on checkout integration. Your end customers are hundreds of millions of Amazon shoppers discovering products via Buy for Me and Shop Direct. The core problem you solve is reliably extracting accurate offer data at internet scale from an adversarial environment.

    About the team

    The OAS Offers Tech team makes external merchant products discoverable and purchasable on Amazon. We extract, structure, and serve product offers from hundreds of thousands of websites that were never built for machine readability. Our engineers and scientists work at the intersection of generative AI and distributed systems, solving extraction challenges in an adversarial environment at internet scale. The culture is ownership driven and builder oriented. Engineers own systems end to end, ship fast, and invest in tooling that makes the team stronger. Knowledge sharing through recorded sessions and peer mentoring keeps the team resilient as we grow.

    Numbers & Facts

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

    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

    Skills

    • Amazon Alexaunmatched
    • Artificial Intelligence (AI)unmatched
    • Automationunmatched
    • Coachingunmatched
    • Code Reviewsunmatched
    • Customer Relationsunmatched
    • Data Managementunmatched
    • Data Qualityunmatched
    • Deep Learningunmatched
    • Distributed Computingunmatched
    • Healthcareunmatched
    • High Availabilityunmatched
    • Internet Applicationunmatched
    • Large-Scale Systemsunmatched
    • Machine Toolunmatched
    • Mentoringunmatched
    • Modeling Languagesunmatched
    • Problem Solving Skillsunmatched
    • Product Lifecycleunmatched
    • Prototypingunmatched
    • Service Level Agreement (SLA)unmatched
    • Software Developmentunmatched
    • Software Engineeringunmatched
    • Technical Strategyunmatched
    • Technical/Engineering Designunmatched
    • Testingunmatched
    • Training Data Setsunmatched
    • Unstructured Dataunmatched
    • Web Browsersunmatched
    • Website Conversionunmatched

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