AmazonSoftware Dev Engineer, AWS Identity Analytics
Amazon is hiring a Software Dev Engineer, AWS Identity Analytics 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
- On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions AI agents among its tools and skills.
- Level classes it as a mid-level role.
- Amazon has 20,000+ other open roles on Level.
- Posted in the last few days.
AI in this role
Our platform is the foundation on which everything else stands: ingesting petabyte-scale data from dozens of Identity services, transforming it into structured, queryable intelligence, and serving it reliably to the ML models, LLM agents, and dashboards that our customers act on every day.
Are you excited by the prospect of building AI-powered solutions that let stakeholders access insights without needing to understand how the underlying data is organized or connected? Do you want to work on petabyte-scale data processing, enrichment, and querying engines? Do you want to work on a platform that directly shapes how AWS Identity services evolve — influencing decisions that affect hundreds of millions of customers globally? Do you thrive in ambiguous, fast-paced environments where your engineering work drives measurable business outcomes?
As a Software Development Engineer II on the Identity Analytics team, you will implement and optimize features across our data platform, spanning software, data management, cloud infrastructure, ML models, and AI-powered solutions. You will design and operate the ingestion, transformation, and serving pipelines that feed our ML models and LLM-powered agents. You will partner closely with our Machine Learning Engineers to turn models and prototypes into production-ready systems that run reliably at scale. What makes this role distinct is the combination of hands-on platform engineering with direct impact on our AI capabilities: the features you deliver and the pipelines you operate shape the quality, freshness, and reliability of every insight our customers receive
Key job responsibilities
* Implement, test, and optimize features across the data platform, including software services, data management, cloud infrastructure, ML models, and AI-powered solutions.
* Design, build, and operate ingestion, transformation, and serving pipelines that feed ML models and LLM-powered agents.
* Partner with Machine Learning Engineers to turn models and prototypes into reliable, production-ready systems.
* Improve data quality, freshness, and reliability through monitoring, alerting, and automated validation.
* Take part in on-call, troubleshoot production issues, and drive root-cause fixes for your components.
* Write clear design documents for features and components, and take part in design and code reviews.
* Help improve the team's engineering practices, and mentor SDE I engineers and interns.
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
- Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
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 Dev Engineer, AWS Identity Analytics at Amazon rates 66 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● 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
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI agents. 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.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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