Software Development Engineer, AWS AI Agentic Automated Reasoning

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 1+ years of software development engineer or related occupational experience
- 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
- 1+ years of Object Oriented Design experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
- Experience programming with at least one software programming language
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

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The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually
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.

We are seeking a talented and passionate 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 an SDE, you will design, build, and operate components of Amazon's cloud-hosted automated reasoning platform that enables AWS services to offload satisfiability and verification queries at scale. You will tackle challenges in distributed systems, solver integration, API development, 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 strong software engineering skills with automated reasoning technology. You'll work alongside world-class scientists and senior 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 your contributions will be highly visible.

Key job responsibilities
- Design and implement features and components of Amazon's cloud-hosted automated reasoning platform, including query routing, solver orchestration, result caching, and soundness management.
- Build and maintain distributed systems that meet AWS's operational excellence standards for availability, latency, and correctness.
- Contribute to the evolution of the service API, making it easier for customers to integrate reasoning capabilities into their workflows.
- Collaborate with Automated Reasoning scientists to integrate solver improvements and new capabilities into the production platform.
- Participate in on-call rotations, build monitoring and alerting, and contribute to the continuous improvement of service reliability.
- Write clean, well-tested, production-quality code and participate actively in code reviews and design discussions.
- Work with internal AWS customer teams to understand their use cases and help troubleshoot integration issues.

A day in the life
A typical day may include implementing a new feature for the solver service, collaborating with a scientist on integrating a solver optimization, participating in code reviews, debugging an issue in the query pipeline, or writing tests to improve coverage. You'll spend most of your time writing code and solving technical problems, while also contributing to design discussions and operational improvements. You might also attend a sprint planning session, pair with a teammate on a tricky problem, or investigate a customer-reported issue.