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Technical Product Owner ID70119
AgileEngine
Miami, FL
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Fort Lauderdale, FL
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Technical Product Owner ID70119
AgileEngine
West Palm Beach, FL
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Technical Product Owner ID70119
AgileEngine
Blacksburg, VA
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Boca Raton, FL
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Jacksonville, FL
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Jersey City, NJ
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Tampa, FL
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Baltimore, MD
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Technical Product Owner ID70119
AgileEngine
Orlando, FL
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Boston, MA
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Houston, TX
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Austin, TX
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Irving, TX
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Richmond, VA
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
San Francisco, CA
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Atlanta, GA
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Port Charlotte, FL
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Texas City, TX
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Tallahassee, FL
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
New York, NY
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Chicago, IL
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
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Technical Product Owner ID70119
AgileEngine
Dallas, TX
- Hands-on Technical Fluency: Ability to read code, discuss system integrations, and evaluate API designs and data flows directly with engineering pods.
Added 6 mins ago
Staff Full-stack Engineer - Shopping (Remote-eligible)
Capital One
Raleigh, NC
As a Staff Engineer at Capital One, you will be part of a community of technical experts working to define the future of banking in the cloud. You will work alongside our talented team of…
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Data Scientist 1
Baylor Scott & White Health
Raleigh, NC
…Baylor Scott and White is the largest not-for-profit healthcare system in Texas that empowers you to live…

Amazon

Senior Accelerator Engineer, Cloud AI/ML server team

Denver, CO, United States

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Job details

Experience: 7+ years of hardware design and development experience for server, compute, or large-scale infrastructure platforms
Posting language: English
Posted: Aug 28, 2026

Original job description

Description

Application deadline: Nov 5, 2026

Do you want to become the go-to GPU expert for the world's largest Artificial Intelligence accelerator fleet, and grow that expertise faster than anywhere else in the industry?

This is a role where you will deepen your GPU expertise at a pace and scale that doesn't exist outside of hyperscale cloud, working directly with the industry's leading GPU vendors, analyzing behaviors across hundreds of thousands of accelerators, and defining standards that govern production deployment. If you have started to develop GPU or accelerator depth and want a position where you own the full lifecycle at fleet scale, this is the role!

AWS Hardware Engineering is looking for a Senior Hardware Development Engineer to own the technical roadmap across all AI accelerator platforms in the organization. You will be the single-threaded owner of GPU lifecycle from defining hardware, firmware and diagnostics requirements, qualification through field operations and translating fleet-scale failure data into vendor action.

Key job responsibilities

GPU Component Lifecycle & Strategy

Own the technical relationship with vendors across all platforms in the portfolio: roadmap alignment, escalations, partnerships.
Own qualification of new GPU SKUs and baseboard assemblies during NPI bring-up -- define test plans, acceptance criteria, and production readiness gates
Define and maintain GPU firmware qualification criteria across the org -- pass/fail gates, staged rollout policy, regression detection methodology
Drive RMA strategy: build failure evidence packages, negotiate acceptance criteria with vendors, manage submission quotas and pipeline velocity

Fleet-Scale Failure Analysis

Lead root-cause analysis on fleet-wide GPU failure modes (component errors, PCIE interface errors, thermal events, link degradation, manufacturing escapes) using telemetry, event log data, and vendor diagnostics
Set GPU health standards: define the metrics, thresholds, and alerting that platform teams execute against
Define GPU fleet health dashboards: identify relevant telemetry, failure rate trends, replacement pipeline status, firmware version distribution, qualification status

Vendor Engagement & Cross-Team Leadership

Represent the organization in technical discussions with leading vendor’s engineering -- translate fleet-scale patterns into prioritized vendor action items
Partner with server teams to ensure consistent GPU operational practices; provide expertise without owning their execution
Present GPU fleet health, replacement pipeline status, and qualification progress to senior leadership (VP-level) regularly
Mentor engineers on GPU failure analysis methodology

A day in the life

No two weeks look the same. You might be engaging with our GPU vendor's engineering team on future roadmap options and how upcoming architecture changes affect our technical strategy. You might be defining technical requirements to enable AWS to optimize how we deploy and manage GPUs at scale -- translating fleet failure patterns into firmware feature requests. You might be analyzing thermal and error behaviors across tens of thousands of systems to develop predictive models that catch failures before they impact customers. Or you might be building the data package that proves a manufacturing defect to a vendor and recovers millions in component value.

What's consistent: you are the GPU component owner. You see every failure mode, every firmware release, every new SKU qualification. You develop expertise at a rate that isn't possible when you only see one system at a time -- here you see hundreds of thousands, and you use that scale to become the person both AWS and our vendors turn to for answers.

Located in Cupertino, Seattle, or Denver, you work with global hardware teams, vendor engineering, and cross-AWS accelerator initiatives.

About the team

AWS Hardware Engineering designs and delivers next-generation cloud infrastructure -- the servers, accelerators, and storage platforms that power AWS. Our team builds and operates custom AI accelerator systems at global scale, spanning GPU platforms from manufacturing through multi-year fleet operations. We are directly responsible for the most expensive and supply-constrained components in the AWS fleet.

Basic Qualifications

Bachelor's degree in electrical engineering, computer engineering, or equivalent
Experience in developing functional specifications, design verification plans and functional test procedures
7+ years of hardware design and development experience for server, compute, or large-scale infrastructure platforms

Preferred Qualifications

7+ years hardware engineering experience
Direct experience with data center GPUs and associated tooling
Experience developing or influencing server roadmap
Track record of influencing vendor engineering priorities through failure evidence
Familiarity with GPU thermal management, power delivery, and PCIe and interconnect architectures
Experience with firmware lifecycle management at scale (qualification, staged rollout, regression detection, rollback)
Comfortable presenting to VP-level audiences
Experience working horizontally across multiple platform teams without direct authority
Strong data analysis skills at fleet scale (statistical failure modeling, trend detection, threshold setting)

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 Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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, CA, Cupertino - 183,000.00 - 247,600.00 USD annually

USA, CO, Denver - 159,200.00 - 215,300.00 USD annually

USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually

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