Software Development Engineer III, AWS AI/ML Servers

Amazon is hiring a Software Development Engineer III, AWS AI/ML Servers in Seattle, United States. It pays $168k-$227k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this software engineer role is Little AI ●○○○: aI is not part of the work.
The listed pay starts close to the typical software engineer posting on Level.
Level classifies it as a mid-level role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

AWS runs the world's largest fleet of AI/ML accelerator servers. When a model with billions of parameters trains across a large scale of GPUs, the software that provisions, monitors, and heals that fleet is what keeps training on track. We build the services, control planes, and data platforms that turn hundreds of thousands of servers into a reliable, self-managing system. If you want to build software at the intersection of large-scale distributed systems and the physical infrastructure powering frontier AI, this is the role.

We are seeking a Software Development Engineer to design and build the software that operates our accelerated compute fleet: fleet-management services, orchestration and remediation control planes, telemetry and analytics pipelines, and the APIs and tools that engineering, operations, and partner teams depend on. You will own software from design through production, working across multiple teams and organizations to deliver scalable, reliable services.

What You Will Do

You will design and build distributed services and data platforms that manage the fleet end to end. You will turn ambiguous problems into well-architected software: designing APIs, choosing data models, making the latency, availability, and cost trade-offs that come with operating at fleet scale. You will build the control planes that automate provisioning, health evaluation, and remediation, and the pipelines that transform raw telemetry into signals other teams act on. When your service catches and routes a failing node automatically before it disrupts a training job, that is your impact.

Why You Will Love It

Your software runs across a large scale of servers in the cloud, and you see its impact on fleet availability within days of shipping. You solve genuinely hard distributed-systems problems, own services end to end, and work close enough to the hardware to understand exactly what your software is managing. The team is small enough that your design decisions shape the architecture, and large enough that you always have experts to learn from across software, hardware, and operations.

The Ideal Candidate

You are a strong software engineer first: you design clean abstractions, write high-quality, testable code, and reason about correctness, scalability, and failure modes. You care about the customer of your software, whether that is an operations engineer, a partner service, or an internal tool user. You communicate clearly, raise the engineering bar for your team, and can partner with hardware, firmware, and operations engineers to build software that reflects how the fleet actually behaves.

Key job responsibilities
Service & Platform Development

1. Design, build, and operate scalable distributed services and control planes that automate fleet provisioning, health evaluation, and remediation across a large scale of servers
2. Design APIs, data models, and system architectures that balance latency, availability, durability, and cost at fleet scale
3. Own software end to end: design, implementation, testing, deployment, and production operations, following engineering best practices for code review, source control, and CI/CD

Data & Telemetry Platforms

1. Build data and telemetry pipelines that ingest, correlate, and transform signals from across the fleet into actionable insights and automated actions
2. Develop analytics and reporting services, dashboards, and alerting that give engineering and operations teams real-time visibility into fleet health
3. Apply appropriate algorithms and data structures to process high-volume telemetry efficiently and reliably

Reliability & Operational Excellence

1. Instrument services for observability; participate in post-incident reviews, identify contributing causes, and drive permanent software fixes that eliminate whole classes of risk
2. Improve the resilience, performance, and cost of the services you own, and reduce operational load through automation
3. Produce clear, maintainable documentation for services, APIs, and runbooks so others can operate and extend your work

Technical Leadership & Collaboration

1. Decompose complex problems into well-scoped components that you and other engineers can deliver in parallel
2. Partner with systems, firmware, hardware, and operations engineers to translate fleet behavior into software requirements and correct abstractions
3. Review designs and code, mentor engineers, and set engineering standards for the team

May require occasional (<10%) regional and international travel to Design and Manufacturing Partner sites.

A day in the life
You start the day reviewing a design document for a new remediation control-plane API, leaving feedback on the data model and failure handling. Mid-morning, you pair with a teammate to debug elevated latency in the telemetry ingestion service and ship a fix. In the afternoon, you review overnight metrics from a service you own, then write code for a new fleet-health scoring pipeline. You end the day in a design review with a partner team, aligning on the API contract your service will expose to their tooling.

About the team
The Hardware Engineering AI/ML UltraServer platform team is a group of engineers and technical program managers directly responsible for launching GPU-accelerated servers into the AWS fleet. Located in Seattle, Austin, and Cupertino, we collaborate with global development teams and ODM partners to deliver next-generation AI/ML infrastructure deployed in datacenters worldwide. We move fast with small, empowered teams delivering end-to-end, from server conception through fleet-scale operations.

Basic qualifications

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience

Preferred qualifications

- 5+ 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
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience leading the design, development and deployment of business software at scale or recent hands-on technology infrastructure, network, compute, storage, and virtualization experience
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience taking a leading role in building complex software or computing infrastructure that has been successfully delivered to customers
- Familiarity with the infrastructure the software manages, such as Linux, server hardware, BMC/IPMI, or GPU/accelerator platforms

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 - 168,100.00 - 227,400.00 USD annually

How we rate this

Software Development Engineer III, AWS AI/ML Servers at Amazon rates 18 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● 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.