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ZipHQ, Inc. in San Francisco is searching for an experienced Tech Lead to oversee the Core Infrastructure team. This role will involve managing Zip’s Kubernetes platform and collaborating with teams across regions for multi-region expansion.
The ideal candidate will have significant software engineering experience, particularly in areas like infrastructures and observability. The position offers a competitive salary range of $160,000 - $210,000 and opportunities to develop within a cutting-edge AI platform.
Zip is the AI platform for enterprise procurement — built for humans and agents working together. By orchestrating procurement across teams, tools, and suppliers with the help of AI agents, companies can secure the resources they need to innovate faster than ever before.
The world’s most influential enterprises trust Zip, including T-Mobile, OpenAI, AMD, Mars, Dollar Tree, and more. Together they’ve saved over $8 billion and processed over $500 billion in spend.
Zip’s team includes product leaders from Apple, Airbnb, and Meta, as well as former procurement leaders from United Health, Sanofi, MGM Resorts, Discover, and NASA.
Backed by Adams Street, Alkeon, BOND, CRV, DST, Tiger Global, and Y Combinator, Zip has raised $371 million, most recently at a $2.2 billion valuation and has been recognized by Forbes Fintech 50, Fast Company's Most Innovative Companies, Inc. Best in Business, and LinkedIn Top Startups.
We are looking for an experienced Tech Lead to lead the Core Infrastructure team in San Fransisco, California. This role involves taking ownership of Zip’s Kubernetes platform, observability and deployment tooling. You will partner with the Core Infrastructure Toronto, Canada, team to drive Zip’s multi-region expansion, and will also serve as site lead in SF for the broader Foundations Engineering Group.
You will join a super talented Infrastructure team and take ownership in one or more of the following areas:
The salary range for this role is $160,000 - $210,000. The salary for this position is determined based on a variety of job‑related factors that may include location, relevant experience, education, or particular skills and expertise.