Member of Technical Staff, Infrastructure Engineer

Pallet•San Francisco, CA

1d•$200,000 - $265,000•Onsite

About The Position

Pallet is building AI Agents to transform the physical economy — a $12 trillion global industry. We’ve raised $50M from top investors, including General Catalyst, Bessemer Venture Partners, and Bain Capital Ventures. In under two years, we’ve achieved 700% revenue growth and are just getting started. Our mission is to increase the efficiency of the global supply chain by automating the manual workflows that slow supply chain teams down — from scheduling and appointment setting to data entry and load management. Our flagship platform provides end-end visibility, control, and optimization, while our newest product, CoPallet, introduces AI Agents that can understand and execute requests in real time and integrate directly with customer systems. As companies across the physical economy look to generative AI to drive efficiency, many are turning to Pallet to lead the way. With deep supply chain expertise and cutting-edge AI capabilities, we’re positioned to build the next $10B company powering the physical economy. Join us and work alongside leaders from Google, DoorDash, YC, and more to shape the future of supply chain technology. This role is about scaling Pallet's infrastructure to meet the demands of millions of AI agent runs per day. The Infrastructure Engineer will tackle complex scaling and reliability challenges, set technical direction for the company's infrastructure, and own systems that are critical to the business. This is a unique opportunity to join an early-stage, well-funded startup and have significant scope and ownership in a foundational role.

Requirements

5+ years in infrastructure, platform, or SRE roles, ideally at a company or team you joined early and helped scale. Depth and judgment matter more to us than the exact years of experience.
Real depth in at least one area: databases, distributed systems, cloud infrastructure, observability, or application frameworks and runtimes. We value hard-earned production scars over buzzwords.
A track record of grounding decisions in evidence: setting SLOs, prioritizing performance work, planning capacity, finding bottlenecks, and understanding where systems break.

Nice To Haves

Some experience with our stack of TypeScript, Postgres, Redis, Google Cloud, OpenTelemetry, and Datadog.

Responsibilities

Help us scale to millions of AI agent runs per day, solving the capacity, performance, and reliability challenges that come with it.
Make our platform portable across clouds and on-prem customer environments.
Work through complex enterprise integration requirements, including identity, private networking, certificate-based authentication, and data residency.
Own observability and incident response, from alerting and on-call to post-mortems, and make sure the same thing doesn’t break twice.
Improve developer productivity by making local development, CI, deployments, and production debugging fast and dependable.