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Sr. Software Development Engineer, AWS AI Agentic Automated Reasoning (AR)

Amazon.com Inc

  • Seattle, WA
  • 2 days ago

    Highlights

    A typical day may include diving deep into a distributed systems design for a new feature, collaborating with AR scientists on integrating a solver optimization, reviewing code from teammates, debugging a latency issue in the query pipeline, or meeting with a customer team to understand their verification needs. We are seeking a talented and passionate Senior Software Development Engineer (SDE) who wishes to work at the intersection of Automated Reasoning and cloud-scale distributed systems, building and operating managed reasoning infrastructure that powers correctness guarantees across AWS.

    Numbers & Facts

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

    Description

    We are building exciting new capabilities in the Amazon Web Services (AWS) Agentic AI Automated Reasoning group by using Automated Reasoning in new, novel and exciting ways to enhance AWS services. The position is based in Seattle, Washington. As AI workloads become more prevalent, the ones having accurate results will be differentiated from others.

    We are seeking a talented and passionate Senior Software Development Engineer (SDE) who wishes to work at the intersection of Automated Reasoning and cloud-scale distributed systems, building and operating managed reasoning infrastructure that powers correctness guarantees across AWS.

    As a Senior SDE, you will design, build, and operate Amazon"s cloud-hosted automated reasoning platform that enables AWS services to offload satisfiability and verification queries at scale. You will work on challenges spanning distributed systems, solver performance optimization, API design, and service reliability. Your work will directly enable customers to verify correctness of software, infrastructure configurations, and AI-generated code at AWS scale.

    This is a unique opportunity to combine deep systems engineering with automated reasoning technology. You"ll work alongside world-class scientists and engineers to turn research breakthroughs in solver technology into production services that power correctness guarantees for millions of customers. The problems are hard, the impact is enormous, and the team is small enough that your contributions will be highly visible.

    Key job responsibilities

    • Design and implement core components of the managed cloud automated reasoning service, including query routing, solver orchestration, result caching, and soundness management.
    • Build and maintain high-availability, low-latency distributed systems that meet AWS"s operational excellence standards.
    • Develop and evolve the service API to reduce friction for customers migrating from local solvers, and to support new reasoning use cases (including Agentic AI correctness verification).
    • Partner with Automated Reasoning scientists to translate research advances in solver technology into production-ready capabilities.
    • Drive operational excellence-own on-call responsibilities, build monitoring and alerting, automate deployments, and continuously improve service reliability.
    • Mentor junior engineers, contribute to technical design reviews, and raise the bar on engineering practices across the team.
    • Work with internal AWS customer teams to understand their reasoning workloads, troubleshoot integration issues, and optimize performance for their use cases.

    A day in the life

    A typical day may include diving deep into a distributed systems design for a new feature, collaborating with AR scientists on integrating a solver optimization, reviewing code from teammates, debugging a latency issue in the query pipeline, or meeting with a customer team to understand their verification needs. You"ll balance hands-on coding with technical leadership-writing design documents, leading architecture discussions, and mentoring others. You might also participate in operational reviews, work on automating deployment pipelines, or prototype a new approach to scaling solver workloads.

    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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