System Hardware Engineer, Graviton Platform

Amazon is hiring a System Hardware Engineer, Graviton Platform in Haifa, Israel. Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this role Little AI ●○○○: aI is not part of the work.
Level classes it as a senior role.
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AI in this role

Annapurna Labs, as part of Amazon, is looking for a Sustaining Lead Engineer to join the team responsible for maintaining and improving the manufacturing health of our cloud server platforms at scale.

As a Sustaining Lead Engineer, you will own the ongoing producibility, yield, and quality of Amazon Graviton server products across high-volume manufacturing sites — driving root-cause analysis, process improvements, and supply continuity for products already in mass production. This is a multidisciplinary role spanning hardware, firmware, test, and manufacturing process domains.

Key job responsibilities
- Support new product introduction (NPI) to volume transition by defining production-readiness criteria and validating manufacturing processes at scale
- Own manufacturing yield, quality, and reliability metrics for Graviton server platforms in volume production; drive systematic root-cause analysis and corrective actions for field and factory issues
- Partner with Contract Manufacturers (CMs) to monitor process health, resolve production escapes, and implement continuous improvement initiatives across multiple high-volume lines
- Lead debug and failure analysis of field returns and fleet-level reliability events — identify systemic failure modes, develop containment actions, and drive permanent fixes back into design and manufacturing processes
- Partner with supply chain to review, identify, and qualify second-source electrical components to mitigate supply-chain risk and ensure continuity of supply without disrupting production
- Develop and maintain sustaining test strategies — including failure analysis workflows, screening methods, and data-driven disposition criteria — to protect outgoing quality
- Analyze manufacturing and field data at scale to identify trends, repeat-offender units, and systemic failure modes; translate findings into actionable design or process changes
- Willing to travel 4–6 times annually for week-long trips to manufacturer sites

Basic qualifications

- Bachelor's degree in electrical engineering or equivalent
- 8+ years of experience developing and supporting hardware products
- Demonstrated experience leading cross-functional efforts across HW, FW, test, and manufacturing teams
- Working knowledge of server or complex electronic system architecture (PCB, power delivery, high-speed interfaces such as DDR4/5, PCIe Gen3/4/5)
- Hands-on experience with manufacturing test development, debug, and data analysis at scale
- Familiar with scripting (Python/Bash) for practical uses such as data analysis

Preferred qualifications

- Experience working directly with Contract Manufacturers (CMs) or ODMs in a sustaining or production engineering capacity,
- Volume manufacturing — including yield management, failure analysis, root-cause investigation, and corrective/preventive action processes
- Knowledge of networking, storage, or Linux at a system level
- Track record of technical leadership in a matrixed, multi-site environment

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.

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How we rate this

System Hardware Engineer, Graviton Platform at Amazon rates 37 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.