AmazonSoftware Development Engineer, Amazon Quick Suite
Amazon is hiring a Software Development Engineer, Amazon Quick Suite in Seattle, United States. It pays $144k-$194k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include Bedrock, AWS and Ecs.
- Level classifies it as a mid-level role.
- Level lists 20,000+ other open roles at Amazon.
AI in this role
Design and build distributed machine learning systems and ingestion pipelines for retrieval-augmented generation technology.
Key job responsibilities
As a Software Development Engineer, you will be responsible for designing, developing, testing, and deploying distributed machine learning systems and large-scale solutions for our world-wide customer base. In this role, you will collaborate closely with your team to influence our overall strategy and define the team’s road map. You will also drive the system architecture, spearhead best practices that enable a quality product, and help coach and develop junior engineers. A successful candidate will have an established background in engineering large scale software systems, a strong technical ability, great communication skills, and a motivation to achieve results in a fast paced environment.
A day in the life
As a Software Development Engineer on the AWS Quick RAG team, you'll start your day reviewing system metrics and performance dashboards to ensure our ingestion pipelines are processing millions of documents efficiently. You'll spend time coding—whether building new features for multi-modal content processing, optimizing retrieval algorithms, or debugging complex distributed systems issues. Throughout the day, you'll collaborate with applied scientists on machine learning model integration, participate in design reviews with partner teams, and contribute to architectural decisions that shape how customers interact with their data. You'll also mentor junior engineers through code reviews and technical discussions, balancing hands-on development with the opportunity to influence the technical direction of a product used by thousands of enterprise customers.
About the team
The AWS Quick RAG team is responsible for building and maintaining the intelligent document processing backbone of Amazon Quick Suite. We develop scalable ingestion pipelines that handle millions of documents across multiple modalities—PDF, audio, video, tables, and more—using advanced computer vision and machine learning techniques. Our work directly powers Quick Suite's search and retrieval capabilities, enabling enterprise customers to unlock insights from their data. We're a collaborative, innovation-driven team that values technical excellence, operational rigor, and customer obsession, working closely with applied scientists, product managers, and partner teams across AWS to deliver features that transform how organizations interact with their information.
Basic qualifications
- 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
Preferred qualifications
- 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
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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
How we rate this
Software Development Engineer, Amazon Quick Suite at Amazon rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- This job starts at
- $144k
- Typical software engineer job
- $167k
This posting starts 14% below the typical software engineer job. See software engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- What are the limits of Bedrock that you've run into, and how did you work around them?
- What's a project where you used AWS hands-on?
- Walk me through how you've used Ecs in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, Computer vision, Bedrock, AWS, and Ecs. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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