Infrastructure Engineer

Own the full multi-region GPU infrastructure stack end to end as the sole infra hire - 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 (9am-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

• 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 (9am-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, * 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

Pulled from the full job description

• Paid housing
• Food provided
• Dental insurance
• Visa sponsorship, * 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.

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 - 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 · 1-10 people · Industry: AI Tools / LLM infrastructure