Sr Systems Development Engineer, AWS Hardware Engineering Services, AI UltraServers

AWS runs the worlds largest fleet of AI/ML accelerator servers. When a model with billions of parameters trains across a large scale of GPUs every minute of downtime costs real progress. We are building the automation diagnostics and predictive intelligence that keeps this fleet running at peak. If you want to work at the intersection of hardware software and scale where your code directly prevents customer-impacting failures this is the role.

We are seeking a Systems Development Engineer to build automation software diagnostic tooling and fleet health infrastructure for our accelerated compute platforms. You will work across multiple teams and organizations to design scalable reliable systems for our accelerated compute fleet.

What You Will Do

You will tackle problems no one has fully defined yet spanning hardware firmware kernel and software simultaneously. You will own systems end to end writing code that prevents failures rather than reacts to them and building automation that replaces manual toil with intelligent self-healing. You will work across PCIe topology GPU diagnostics Linux drivers and telemetry pipelines to correlate signals and isolate faults at fleet scale. When your system catches a failing GPU before a training job crashes that is your impact.

Why You Will Love It

Your automation runs at a large scale across servers in the cloud. When you ship you see failure rates move within days. The team is small enough that your decisions shape the architecture and large enough that you will always have experts to learn from across hardware firmware and software.

The Ideal Candidate

You know the full stack from bare-metal to userland. You debug at the intersection of components not just within them. You build at cloud scale and care how your systems decisions impact customers. You are an excellent communicator who can drive alignment across hardware software and operations teams.

Key job responsibilities
Fleet Health & Predictive Infrastructure

1. Build and own the automation infrastructure for accelerator (AI/ML) fleet health at a large scale of servers driving toward zero-touch operations that detect diagnose triage and remediate faults without human intervention
2. Design and develop test frameworks test coverage strategies and diagnostic tooling to validate hardware functionality detect faults and ensure qualification coverage across the platform lifecycle.
3. Design predictive failure detection using telemetry sensor data error trending and log correlation to identify degrading components before customer impact
4. Develop monitoring dashboards and alerting for real-time fleet health visibility across manufacturing lab and production environments
5. Define and track fleet health metrics: failure rates mean time to detect and resolve issues first-time fix rate test dwell time and predictive accuracy

Debugging & Troubleshooting

1. Debug complex system-level issues across compute GPU and networking in production including Linux boot/runtime failures PCIe power NIC NVMe and GPU subsystems on x86 and ARM
2. Perform root cause analysis correlating across firmware kernel driver and physical layer; feed findings into manufacturing quality and design improvements

Systems Development & Automation

1. Design scalable test automation for hardware bring-up regression and qualification reducing manufacturing test cycle times without sacrificing coverage through intelligent test sequencing and parallel execution
2. Build data pipelines correlating test results sensor telemetry and component-level data to identify systemic yield issues and drive upstream fixes
3. Develop and maintain Linux device drivers on ARM and x86; work with OS internals and accelerator/GPU software stacks
4. Build and manage tests covering all functional aspects of the system and CI/CD pipelines for rapid deployment to manufacturing lines and production fleet

Cross-Team Collaboration

1. Work across engineering teams and internal customers to ensure new accelerated compute hardware meets data path control path and onboarding requirements
2. Engage with ODMs and design partners on testability diagnostic coverage and automation requirements during hardware design and bring-up phases influencing functional and performance readiness of the platform
3. Partner with datacenter operations to close the loop between field failures manufacturing escapes and design improvements

Operational Excellence

1. Participate in post-incident reviews identify contributing causes and drive permanent fixes that eliminate whole classes of risk
2. Produce clear maintainable documentation for systems runbooks and automation to enable others to operate and extend your work
3. Drive process improvements that increase team agility reducing development friction eliminating unnecessary gates and improving delivery velocity

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

A day in the life
You start the day reviewing overnight validation run results triaging a cluster of GPU errors that correlate with a specific firmware version. Mid-morning you push a fix to your diagnostic automation pipeline and validate it catches the failure pattern in your test the afternoon you join a hardware bring-up call with your ODM partner to debug a PCIe link training failure on a new EVT board walking the team through kernel logs and signal integrity data. You end the day reviewing a pull request from a teammate on a new telemetry correlation engine and updating your manufacturing test coverage dashboard with the latest yield data.

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.

- 6 years of programming with at least one modern language such as C C# Java Python Golang PowerShell Ruby experience
- 6 years of non-internship professional software development experience
- 6 years of designing or architecting (design patterns reliability and scaling) of new and existing systems experience
- 5 years of deploying and operating in a Linux/Unix environment experience
- 6 years of systems design software development operations automation and process improvement experience
- Bachelors degree in Computer Science Computer Engineering Electrical Engineering or equivalent work experience

- 5 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
- Masters degree or PhD in Computer Science Electrical Engineering or a related field
- Track record leading delivery of complex software or computing infrastructure at production scale while also delivering through others by force-multiplying engineering efforts.
- 5 years of experience building end-to-end automation for telemetry-based anomaly detection and intelligent remediation at fleet scale.
- Hands-on experience troubleshooting and debugging system integration and low level issues across server and GPU/accelerator hardware BMC/IPMI firmware PCIe topology driver integration and hardware-level fault isolation
- Experience working with ODMs or hardware design partners on NPI validation
- Experience working in large-scale datacenter or cloud environments and setting engineering best practices and operational standards across multiple teams.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees supervisors and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees supervisors and staff to ensure exceptional customer service; and follow all federal state and local laws and Company policies. Criminal history may have a direct adverse and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above as well as the abilities to adhere to company policies exercise sound judgment effectively manage stress and work safely and respectfully with others exhibit trustworthiness and professionalism and safeguard business operations and the Companys reputation. Pursuant to the Los Angeles County Fair Chance Ordinance we will consider for employment qualified applicants with arrest and conviction records.

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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 CA Cupertino - 173900.00 - 235200.00 USD annually
USA TX Austin - 151200.00 - 204600.00 USD annually
USA WA Seattle - 151200.00 - 204600.00 USD annually