Member of Technical Staff, Infrastructure
Brainbase Labs
San Francisco, CA · Posted August 13, 2026
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Where San Francisco, CA ranks
Where San Francisco, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for security jobs316 openings · of 20
- #1Best cities for technology jobs7,178 openings · of 100
- #1Best cities for financial services pay after cost of living$173k · of 33
- #1Best cities for entry-level jobs that want AI skills35% · of 100
- #1Best cities for entry-level jobs that want AI skills in the West Coast35% · of 54
- #1Cities with the most jobs that do not need a four-year degree in the West Coast902 jobs · of 47
Rankings about engineering jobs
- Best cities for software and engineering jobs #1 San Francisco (3,412 openings)
- Best cities for engineering pay after cost of living #1 San Mateo ($216k)
- Most requested AI skills in engineering jobs #1 AI tools in daily work (6.1%)
- AI tools named most often in engineering jobs #1 Claude (1.7%)
- Employers with the most engineering jobs #1 Amazon (2,992 roles)
Pay compared with the market
This listing does not state pay. Across 130 open member of technical staff listings that state pay, the middle half runs $208,000 to $270,000 and the median is $240,000.
Listed pay is what employers advertise, not what people are paid.
Member of Technical Staff salaries by state · Check your own pay
How AI is used in this kind of work
Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
About Brainbase
Brainbase is building the primitives for the next 1B agents.
We power internal agents across government, Fortune 500, frontier labs and hyper-growth startups. Teams use our configurable primitives such as evals, observability, router, authentication, permissions, sandboxes, harnesses and more to deploy internal agents at scale securely. We support 8+ harness and 50+ models, including sovereign deployments.
Launches Take a look at some of our previous launches to get an idea of what we’re working on:
- Brainbase platform: https://brainbaselabs.com/blog/brainbase-is-now-ga
- Universal Managed Agents API: https://brainbaselabs.com/blog/universal-managed-agents
- Universal Agent Protocol (UAP) (open-source): universalagentprotocol.io http://universalagentprotocol.io
About the role
Brainbase’s infrastructure consists of a lot of different services for our primitives. These services need to be containerized to run on different environments including our managed cloud, AWS/Azure/GCP and sovereign on-premise deployments, with low latency and high reliability. Some of these services look like Docker containers (e.g. authentication service) while some of them are more complex to control and scale (e.g. sandboxes). You would primarily be contributing to building and improving these infrastructural components.