Sr. Manufacturing Engineer, Design for Manufacturability & Automation, Annapurna AI Systems Manufacturing, Quality and Reliability

AI in this role

The Annapurna AI Manufacturing, Quality and Reliability (MQR) team is part of AWS Annapurna Labs, building the AI platforms that power the world's largest cloud. We take custom silicon from design through high-volume production across multiple ODM and JDM partners in Asia and North America, at a ramp rate and scale that leaves no room to inspect quality in after the fact.

We are looking a Senior Manufacturing Engineer to own Design for Manufacturability and manufacturing automation across our accelerator card, baseboard, and rack programs. Your job is to move quality upstream: make the design manufacturable before the drawing is released, and make the line capable of building and verifying it without manual intervention.

You will sit between hardware design, component suppliers, and ODM process engineering. You will review designs for tolerance capability, land pattern and stencil design, connector retention and insertion, part accessibility, handling, and serviceability — and you will hold the line when a design is not buildable at the yield and rate the program requires. You will then own the automation and metrology strategy that makes the resulting process observable: automated inspection, in-line measurement, fixture design, and the data capture behind it.

Key job responsibilities
Design for Manufacturability
- Own DFM, DFA, and DFT review as a gate prior to drawing release and prior to NPI build, across accelerator cards, baseboards, power distribution, interconnect, and rack-level assembly.
- Perform tolerance stack-up and GD&T analysis, and establish tolerances that a partner factory can hold at Cpk ≥ 1.33 at volume — not tolerances that are theoretically correct and practically unachievable.
- Reconcile component supplier specifications against AWS drawings before release, and resolve conflicts where a supplier's requirement is tighter than the drawing allows.
- Design process margin into the product: solder paste volume against land pattern and via structure, insertion force windows, retention features, and clearance for automated handling.
- Provide design feedback on connector retention, contact-level defect modes, fastener and cable access, and serviceability in the rack.
- Build and maintain a versioned DFM design-rule set that carries across product generations, so each program does not relearn the same lessons.

Manufacturing Automation and Metrology
- Own the automated inspection and in-line measurement strategy — SPI, AOI, AXI, ICT, vision, and dimensional or true-position measurement — including whether each system is capable of detecting the defect it is deployed against.
- Drive measurement system analysis across partners: gauge design, gauge R&R, correlation between AWS and supplier measurement, and elimination of methodology differences that make cross-site data non-comparable.
- Specify and deploy automation that removes manual handling and manual data collection from the line, and automate the capture of measurement and process data into SPC.
- Own test fixture and tooling design, calibration, and health management, including detection of fixtures that induce false failures.
- Assess new ODM lines and new sites for process capability before qualification, and define the equipment and process requirements to close gaps.

Program and Partner Execution
- Partner with hardware and silicon design teams during development to influence the design while influence is still cheap.
- Work directly with ODM and JDM process engineering at multiple sites to implement process changes, and verify in production that they held.
- Drive design and process changes through DCN and ECN, including propagation across all build sites.
- Build mechanisms — control plans, capability studies, design-rule checks, runbooks — that continue to work at sites you are not present at.

About the team
Annapurna Labs is a wholly owned subsidiary of AWS, focused on developing custom silicon and servers including the Nitro, Graviton, Inferentia, and Trainium families of processors. Machine Learning Annapurna (MLA) functions as a vertically integrated team including software, firmware, hardware, and silicon design in a single organization. We are the Annapurna AI Servers and Systems organization under MLA, focused on Hardware Development, Software Development, Fleet Ops Systems, and Manufacturing, Quality, and Reliability. This position is in the Manufacturing, Quality and Reliability team.

Basic qualifications

- Bachelor's degree in Mechanical, Electrical, Manufacturing, or Industrial Engineering
- 7+ years of manufacturing engineering experience on high-volume electronics or server hardware, including ownership of Design for Manufacturability
- Experience with SMT/PCBA manufacturing and system-level assembly at a contract manufacturer, ODM, or JDM
- Experience with tolerance analysis and GD&T, and with establishing manufacturable tolerances validated by process capability data
- Experience specifying or deploying automated inspection or manufacturing automation on a production line
- Experience influencing hardware design teams to change a design for manufacturability reasons
- Willingness and ability to travel internationally to partner manufacturing sites

Preferred qualifications

- Master's degree in Mechanical or Electrical Engineering or a related field
- Experience with server, storage, networking, or large-scale distributed systems
- Experience in high-volume manufacturing operations or sourcing environments
- Experience with robotics work cells and their control systems, or experience working with electrical and mechanical conveyance systems
- Knowledge of project management tools and software
- Experience working with overseas partners
- Depth in SMT process: stencil and land pattern design, paste volume and SPI, reflow profiling, placement equipment, via-in-pad and VIPPO structures
- Depth in press-fit and connector processes, including insertion force, retention, and contact-level defect modes
- Metrology and MSA depth: gauge R&R, true position measurement, laser 3D scanning, CMM, optical measurement, Cpk and SPC
- Working knowledge of IPC standards (IPC-A-610, IPC-7351, IPC-A-600, IPC/WHMA-A-620) and J-STD-001
- DFMEA, PFMEA, control plan, and 8D experience
- Demonstrated ability to uncover systemic manufacturability issues prior to NPI
- Meets/exceeds Amazon's leadership principles requirements for this role
- Meets/exceeds Amazon's functional/technical depth and complexity for this role

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, TX, Austin - 159,200.00 - 215,300.00 USD annually

How we rate this

Sr. Manufacturing Engineer, Design for Manufacturability & Automation, Annapurna AI Systems Manufacturing, Quality and Reliability at Amazon rates 35 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.