G

Gimlet Labs

Serverless AI inference platform with orchestration

Materials and Product Lifecycle Program Manager

Production Planning & SchedulingConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$225k - $300k /yrIn-person

About the Job

Requirements

  • At least 5 years of experience in product lifecycle management, BOM management, materials planning, or hardware operations.
  • Hands-on experience creating internal part numbers and structuring multi-level BOMs, from top-level assemblies down to components.
  • A strong understanding of revision control, engineering change processes (ECR/ECO), and AML/AVL management.
  • Ability to read and interpret datasheets and spec sheets for hardware such as servers, networking gear, power, cabling, and optics.
  • Experience managing EOL notices, PCNs, last-time buys, and excess and obsolete inventory.
  • Experience translating changing deployment schedules into material plans, and managing long-lead components and shortages.
  • Strong analytical skills, advanced spreadsheet experience, and hands-on use of PLM systems such as Arena, Agile, or Windchill and ERP systems such as NetSuite, SAP, or Oracle.
  • Ability to work closely with Engineering while respecting ownership boundaries: Engineering owns design, technical qualification, and substitutions; this role owns part data and BOM integrity.
  • A track record of bringing structure and discipline to fast-moving hardware programs.

Responsibilities

  • Own the full part lifecycle, from new part introduction through active production, end of life, and obsolescence.
  • Monitor manufacturer EOL notices and product change notifications, assess their impact on active and planned deployments, and drive last-time buys or qualified replacements with Engineering.
  • Manage excess and obsolete inventory, including disposition plans that minimize cost.
  • Create internal part numbers using a consistent numbering scheme, and map each to manufacturer part numbers and approved sources.
  • Define and enforce part data standards for descriptions, units of measure, revision levels, lifecycle status, and approved manufacturer and vendor lists.
  • Read and interpret component datasheets and spec sheets to verify key attributes, including form factor, electrical and thermal ratings, compatibility, and compliance, before part release.
  • Build and maintain multi-level BOMs, from top-level assemblies such as racks, servers, and networking down to sub-assemblies and components.
  • Own BOM accuracy by regularly auditing BOMs, reconciling them against what is purchased, received, and deployed, and quickly resolving discrepancies.
  • Control BOM releases and revisions through the engineering change process (ECR/ECO), and assess each change’s impact on open orders, inventory, cost, and delivery.
  • Translate approved deployment plans into time-phased material requirements and purchasing priorities.
  • Track long-lead components, shortages, and material readiness across suppliers and sites.
  • Report material risks and recommended actions to Supply Chain and deployment leaders.
  • Stand up a controlled internal part numbering scheme and part register covering all active deployments.
  • Build released, revision-controlled top-level assembly BOMs for core rack, server, and networking configurations.
  • Establish a BOM accuracy baseline and regular audit process, with a clear target and plan to close gaps.
  • Put an EOL and PCN monitoring process in place for critical components, with last-time-buy or replacement plans for at-risk parts.
  • Define clear handoffs with Engineering for BOM releases and engineering changes.
  • Build a material-readiness view tied to deployment milestones and purchasing priorities.
  • Develop practical PLM and ERP workflows so Engineering, Supply Chain, and deployment teams work from one accurate, current source of part and BOM data.

Desired Qualifications

  • Experience supporting data center, compute, networking, server, semiconductor, or other complex hardware deployments.
  • Experience building a part numbering system, BOM standards, or PLM process from scratch in a fast-scaling company.
  • Experience implementing, migrating, or improving PLM and ERP systems.
  • Experience working across multiple suppliers, contract manufacturers or ODMs, deployment sites, and hardware configurations.
  • An APICS/ASCM certification such as CPIM or CSCP.

About the Company

Gimlet Labs

Serverless AI inference platform with orchestration

Gimlet Labs builds an inference cloud platform that runs and manages complex AI agent workloads across heterogeneous hardware, including GPUs and other accelerators. Its software splits AI tasks and routes each part to the most suitable hardware to improve speed while keeping cost and power use the same. The Gimlet Cloud offers serverless inference for building and scaling multi-agent systems, with the platform handling scheduling and hardware-aware optimization, and it can be deployed in the cloud or in customers’ data centers. It is developing kforge, a toolkit that uses AI agents to automatically generate optimized PyTorch kernels for CUDA, ROCm, and Metal. The goal is to make AI inference a practical, scalable infrastructure problem by coordinating diverse compute to improve performance and efficiency for enterprise workloads.

Company size
51-200
Company stage
Series B
Total funding
$392M
Headquarters
San Francisco, CA
Founded
2023

Recently Posted Jobs

Explore more opportunities at Gimlet Labs

See more jobs