AmazonSenior Systems Engineer, Amazon Special Projects
Amazon is hiring a Senior Systems Engineer, Amazon Special Projects in Seattle, United States. It pays $151k-$205k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include Linux, C and Python.
- Level classifies it as a senior role.
- Level lists 21,000+ other open roles at Amazon.
- The role was posted within the past week.
AI in this role
Designs and implements agent daemons, sandboxes, and GPU caching layers for low-latency ML inference infrastructure.
As the Sr. Systems Engineer, you will own the agent daemon that runs on compute nodes, the runtime sandbox that isolates workloads, and the local storage and caching layer that determines which assets are resident and ready to serve. You will build the detection logic that manages node availability, and the GPU capability reporting that tells the scheduler exactly what each node can handle. Your work directly determines whether the platform can deliver low-latency ML inference — and whether it can do so reliably at scale.
Key job responsibilities
- Design and implement the agent daemon on Linux, including GPU discovery, availability detection, and sandboxed container execution for ML inference workloads.
- Architect the local caching system — eviction policies, versioned manifests, disk budget management, and efficient update mechanisms that minimize data transfer for large model files.
- Build VRAM management and graceful workload migration logic.
- Integrate hardware attestation with the security engineer and support diverse hardware configurations and fleet onboarding automation.
About the team
Amazon Special Projects is a small, high-autonomy team building new-to-Amazon infrastructure from scratch. The systems component is where software meets hardware: you will build the on-node runtime — the agent, sandbox, GPU manager, and local storage layer — that makes a compute node reliable, secure, and performant. This is systems engineering at its most tangible — your code runs on real hardware and must be resilient to everything the real world throws at it.
Basic qualifications
- 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
- Experience leading the design, build and deployment of complex and performant (reliable and scalable) software solutions in production
- 6+ years of systems design, software development, operations, automation, and process improvement experience
- 7+ years of experience in systems programming (Rust, Go, or C++)
- Deep knowledge of Linux internals, including process scheduling, memory management, and storage subsystems
- Hands-on experience with container runtimes (Docker, containers, or custom sandboxes)
- Experience with GPU tooling and management (nvidia-smi, NVML, CUDA runtime)
- Demonstrated ability to build software that runs reliably on heterogeneous hardware
Preferred qualifications
- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
- Experience taking a leading role in building complex software or computing infrastructure that has been successfully delivered to customers
- Experience designing caching systems with constrained storage budgets (LRU, ARC, or custom policies)
- Background in edge computing, fleet management, or embedded systems engineering
- Familiarity with hardware attestation (TPM, TEE) from the device side
- Experience with storage performance profiling and optimization across hardware types
- Track record of building daemon/agent software that operates unattended for extended periods
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 - 151,200.00 - 204,600.00 USD annually
How we rate this
Senior Systems Engineer, Amazon Special Projects 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
Questions you could be asked
- Tell me about a project where systems engineering was part of your work. What did you do?
- Tell me about a project where gpu management was part of your work. What did you do?
- Tell me about a project where containerization was part of your work. What did you do?
- Tell me about a project where ml inference was part of your work. What did you do?
- Walk me through how you've used Linux in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Systems Engineering, GPU Management, Containerization, ML Inference, and Linux. 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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