Infrastructure Eng
Andera
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)
How AI is used in this kind of work
Among computer network architects, AI is already used for some of the tasks. Measured exposure for computer network architects: 20% (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.
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About the job
ABOUT ANDERA
Andera is building reliable AI agents for back-office finance, starting with automating audits for the world's largest public companies.
Audits have resisted automation for decades due to the scale and instability of the underlying data. Large companies generate hundreds of millions of tokens of financial data across massive spreadsheets with constantly changing formats. Even understanding a single document can take expert auditors six or more hours, and a typical audit involves many of them.
We're building agents that can parse, interpret, and reason over data of this complexity—compressing gigabytes of messy financial information into representations that LLMs can work with reliably. The result is turning weeks of manual audit work into minutes of review.
This work requires long-horizon reasoning, robust data systems, and production-grade reliability—and it forms the foundation for automating some of the most complex financial workflows in the world.
FOUNDING TEAM
Andera is built on the belief that this problem can only be solved by pairing elite auditors with elite engineers.
- Engineering team: Alumni of MIT, Berkeley, and Waterloo, with experience at Jane Street, Stripe, Shopify, and Microsoft.
- Audit team: Former #1 performers at Deloitte and leaders of national finance practices at Revolut.
THE ROLE
We're hiring an Infrastructure Engineer to own the systems our agents run on. Audit workloads are bursty and enormous—single engagements push 100GB+ of financial data through our pipelines—so the infrastructure has to scale hard, fail gracefully, and stay observable when it doesn't.
This is a high-ownership role with responsibility from architecture through deployment.
WHAT YOU'LL WORK ON
- Designing and operating the compute and orchestration layer that runs our agents (Temporal, Docker, AWS Fargate)
- Scaling data ingestion and processing pipelines that handle ~100GB+ per engagement without stalling
- Building the observability, alerting, and tracing that make agent failures debuggable in production
- Owning CI/CD, infrastructure-as-code, and deploy safety so engineers can ship many times a day
- Hardening security, isolation, and reliability to the standard our enterprise customers require
WHAT WE'RE LOOKING FOR
- Strong systems engineering fundamentals — You can design concurrent, distributed workloads over large datasets and think carefully about throughput, backpressure, retries, and observability.
- Production infrastructure experience — You've owned cloud infrastructure end to end: provisioning, deploys, monitoring, and the 2am pages that follow.
- Pragmatic automation instincts — You'd rather codify infrastructure than click through consoles, and you know when the simple thing is the right thing.
- Comfort learning non-engineering domains quickly — You can absorb audit concepts from domain experts and turn them into working systems fast.
- Experience with or adjacent to our stack: TypeScript, Python, Temporal, Docker, Terraform, AWS Fargate