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Senior Infrastructure Engineer

david joseph & company โ€ข United State
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AI Summary

Own the full multi-region GPU infrastructure stack end to end as the sole infra hire. Build and maintain super low-latency GPU serving infrastructure. Manage multi-cloud deployments and on-premise enterprise environments.

Key Highlights
Full-stack ownership of multi-region GPU infrastructure
Low-latency GPU serving infrastructure
Multi-cloud and on-premise deployments
Key Responsibilities
Own the full infrastructure stack end to end across multi-region GPU deployments
Build and maintain super low-latency GPU serving infrastructure
Manage multi-cloud deployments, including cloud marketplace integrations and provider relationships
Technical Skills Required
AWS Terraform Docker
Benefits & Perks
$150,000โ€“$250,000 + up to 1% equity
Visa sponsorship
Relocation package

Job Description


San Francisco, CA

  • On-site
  • Full-time Compensation: $150,000โ€“$250,000 + up to 1% equity


About The Company

A seed-stage LLM interpretability and context-optimization company building custom machine learning models that analyze and compress token contexts before they reach the underlying model โ€” delivering roughly 50% inference cost reduction, lower latency, and higher accuracy for the enterprises and scale-ups integrating LLMs into their products. Venture-backed, with strong early traction (:1,000 customers within its first seven months).

Founded 2025

  • 1โ€“10 people
  • Industry: AI Tools / LLM infrastructure


The Role

Own the full multi-region GPU infrastructure stack end to end as the sole infra hire โ€” global low-latency serving, multi-cloud and on-premise deployments, reliability, and cost efficiency. Your work sits directly in the critical path of live customer traffic. This is a high-ownership, in-person role at a fast-moving early-stage team, working a 996 pace (9amโ€“9pm, six days a week) in San Francisco.

What You'll Be Doing

  • Own the full infrastructure stack end to end across multi-region GPU deployments, major public clouds, and on-premise enterprise environments.
  • Build and maintain super low-latency GPU serving infrastructure that sits in the critical path of live customer traffic.
  • Manage multi-cloud deployments, including cloud marketplace integrations and provider relationships.
  • Design and iterate on deployment, scaling, reliability, and cost-efficiency systems as the sole infra owner.
  • Support on-premise deployments for enterprise clients and ensure performance and reliability at each site.
  • Research and adopt new infrastructure solutions continuously as the stack and customer base grow.


Tech stack: AWS, GCP, Terraform, Docker, CI/CD, GPU/ML inference infrastructure

Requirements

  • Own cloud systems serving compression API end-to-end
  • Build and operate global low-latency high-throughput GPU ML inference infrastructure
  • Work with AWS, Terraform, Docker and CI/CD
  • Have built and operated production infrastructure at a startup or larger company
  • Learn new solutions and technologies quickly
  • Improve and research infrastructure solutions continuously
  • Based in or willing to relocate to San Francisco to work in person at the hacker house
  • Willingness to work startup hours in a 996-style environment (9amโ€“9pm, six days a week)


Green Flags

  • Quick learner who grasps products and systems fast
  • Experience building for performance and reliability at scale
  • Research and product focus mindset
  • High ownership mentality
  • Startup-minded operator who prioritizes learning and growth over work-life balance
  • GPU infrastructure experience in production
  • First infra hire at a startup
  • Background at an infrastructure company


Red Flags

  • Infra scope limited to model training pipelines only
  • 20+ years of experience with a slow-moving, process-heavy background
  • Prioritizes work-life balance as a primary requirement
  • No production infra ownership


Why Join

  • Sole infra owner with full-stack ownership from day one, directly in the critical path of live customer traffic.
  • Well-funded seed-stage company with strong early traction and an experienced backer base.
  • Significant equity, housing and food provided at the SF hacker house, visa sponsorship, laundry and cleaning, company off-sites, infinite DoorDash, and health & dental.


Details

  • Location: San Francisco, CA
  • Work policy: In person (SF hacker house); 996 pace โ€” 9amโ€“9pm, six days a week
  • Compensation: $150,000โ€“$250,000 + up to 1% equity
  • Visa sponsorship: Available (H-1B, O-1, OPT)
  • Employment type: Full-time

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