Senior TPM - Manufacturing & Reliability for Accelerators

Amazon Web Services (AWS); Austin (TX); On-site; USD 149,000 - 201,000; Full time

Job summary

Annapurna Labs (U.S.) Inc. is seeking an experienced TPM to manage server and rack manufacturing programs across ODM and CM partners in North America.

You will own build plan attainment, yield, test cycle times, and on-time shipment to datacenter while coordinating with design, manufacturing, quality, and supply chain teams. You will drive cadence with partners, resolve constraints, and gate ramp decisions based on demonstrated yield and cycle time rather than schedule pressure.

Qualifications

• 5+ years of technical product or program management experience.
• 7+ years of working directly with engineering teams.
• Experience managing programs across cross functional teams and release schedules.
• Experience with ODM/CM models and cross-geographic vendors.
• Experience owning manufacturing or operations metrics and driving improvement.

Responsibilities

• Own manufacturing programs end to end across ODM and CM partners.
• Establish operating cadence with each partner and manage commitments.
• Own material readiness, constraints resolution and staging capacity at each site.
• Drive manufacturing readiness for new rack platforms and gate ramp decisions.
• Coordinate across Design Eng., Manufacturing Eng., Quality & Reliability, Supply Chain, Logistics.
• Build reporting layer and provide leadership with weekly status on shipped, at risk, and needed actions.

Skills

Technical product mgmt

Cross-functional collaboration

Vendor management

Metrics ownership

Program management

Job description

Annapurna Labs (U.S.) Inc. is seeking an experienced TPM to manage server and rack manufacturing programs across ODM and CM partners in North America.

You will own build plan attainment, yield, test cycle times, and on-time shipment to datacenter while coordinating with design, manufacturing, quality, and supply chain teams. You will drive cadence with partners, resolve constraints, and gate ramp decisions based on demonstrated yield and cycle time rather than schedule pressure.