Software Development Engineer, AWS Quick

- 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, Bellevue - 143,700.00 - 194,400.00 USD annually
USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually
Amazon Quick is building an AI-native work surface that understands what users want to accomplish and figures out how to get it done. We are looking for a Software Development Engineer II to design and deliver the third-party integrations that connect Quick to the business systems users rely on every day, enabling AI agents to take real action on their behalf. You will lead technical strategy for these connectors, working across teams to solve problems where requirements are clear but the right architecture is not. If you enjoy building systems that must work reliably at enterprise scale and want your code to directly drive product adoption, this is a role where your engineering decisions will have visible impact.

Key job responsibilities
- Design and implement software solutions across the full development lifecycle, including requirements gathering, architecture, coding, testing, deployment, and operational support.
- Write clean, maintainable code using optimal data structures and algorithms, and actively participate in code reviews to elevate the quality of your team's output.
- Identify root causes of operational issues and drive permanent fixes, while continuously improving your team's technical processes and operational health.
- Collaborate with cross-functional partners to understand customer and business needs, translating them into well-scoped technical designs that balance short-term delivery with long-term maintainability.
- Mentor and coach fellow engineers, contribute to clear technical documentation, and help onboard new team members to accelerate their effectiveness.

A day in the life
You will start your day reviewing operational metrics and addressing any alerts from overnight. From there, you might dive into a design discussion for an upcoming feature, pair with a teammate on a tricky code review, or prototype a new approach to a performance bottleneck. You will regularly connect with product and engineering partners to align on priorities and share progress. Expect to balance hands-on coding with collaborative problem-solving, ensuring the software you ship is reliable, scalable, and easy for others to extend.

About the team
The Quick team is on a mission to build an AI-native work surface where users simply express what they want to accomplish and Quick handles the rest, drawing on deep knowledge of the user, their team, and their organization. Our real-time connectors are central to that vision: they drive adoption by giving Quick the breadth and reliability enterprises demand. We value collaboration, technical rigor, and open dialogue. If you want to join an inclusive team where your work directly shapes how people interact with AI at work, we would love to talk.