Cloud infrastructure and DevOps in San Francisco
Cloud credits carry a lot of San Francisco startups through their first year, and then they run out. The bill that arrives is for infrastructure nobody designed: GPU instances left running, three environments that should be one, and a managed service chosen because it was free at the time. The team that built it is busy shipping product.
We go through what is running and what it costs, then fix it in order of savings. That usually means infrastructure defined in Terraform, environments that scale down when idle, inference moved to wherever the price and latency make sense, and deploys from CI with a rollback that works. We run our own product on self-hosted Kubernetes because it is cheaper, and we will tell you plainly whether that trade suits a team your size.
San Francisco's software market is, for now, largely an AI market. The city is home to the best-known model companies and to a much larger layer of venture-backed startups building products on top of their models, alongside the SaaS, fintech and developer-tool companies that were here before. Most buyers are young companies with funding, a deadline set by their next raise, and more product ideas than engineers.
What they need is rarely the model. It is everything around it: queues for requests that take most of a minute, streaming that survives a dropped connection, fallbacks when a provider is rate-limiting, a record of what each request cost, and evaluation sets that tell you whether last night's prompt change made things better or worse. Then, often within months, the first enterprise customer arrives, and its IT team asks for single sign-on, automatic provisioning, roles their own admin can manage and an activity log they can export. A backend built for a demo meeting that list is where many pilots stall. We build the product and the infrastructure that make a model useful to paying customers, and the enterprise layer that turns a pilot into a contract.
Built In puts the average base salary for a software engineer in San Francisco at around $181,000, and the model companies compete for the same people with equity most startups cannot match. For a seed or Series A company, every senior hire becomes a search measured in months, and the roadmap waits while it runs. The work that piles up in the meantime is usually well defined: a provider integration, an admin console, a move to usage-based billing, a mobile companion app. That is the work we pick up in days and deliver in pieces you can judge on their own.
We work from Bengaluru with four hours of live overlap every working day, placed across your morning in San Francisco. Stand-ups, design calls and code review happen in that window, with the engineer who writes the code. Everything decided outside it goes into your repository, your tracker and the architecture notes we write as we go, so you start each day knowing what moved.
We fit best when the work is defined and the roadmap will not wait for a hire: the product and infrastructure around a model, the enterprise features a first large customer asks for, or the months before your next engineer starts. Most teams begin with a fixed-price two-week piece. Agencies can bring us in white-label, under their own name.
Four ways this arrives.
Resources were created in the console over several years and nobody can say which ones matter. We inventory the account, bring what is live into Terraform, remove what is not, and hand you a repository that describes the whole estate.
It is usually idle capacity, oversized instances, forgotten environments and data transfer nobody priced. We find where the money goes, cut the obvious waste where you already are, and only then ask whether a cheaper provider such as Hetzner suits your steady workloads.
One person knows the steps and every release waits for them. We build a pipeline that tests, builds and deploys on merge, with rollback to the previous image, so shipping on a Friday afternoon is a decision rather than a gamble.
The channel fires all day, so everyone has muted it, so real outages are reported by customers. We alert on what users actually feel, route each alert to a named owner, and delete every alert nobody would act on at 3am.
A K3s cluster on Hetzner that we provisioned and are on call for, deployed through Flux, where only a push to master can produce an image production will run.
Read the write-up →Asked by San Francisco teams.
How do you work with teams in San Francisco?+
We are in Bengaluru and overlap with you for four hours every working day, placed across your San Francisco morning. Stand-ups, design calls and code review happen live in that window, with the engineer who writes the code. We work inside your tools: Slack for conversation, GitHub for code and review, Linear for the plan. Anything decided outside the window is written down there, so nothing depends on memory.
Do you build for AI startups?+
Yes. Most of that work sits around the model rather than inside it: retrieval over your own data, evaluation sets that run on every prompt change, streaming interfaces, cost tracking per customer, fallbacks between providers, and logging that explains an answer after the fact. Then comes the enterprise layer your first large customer asks for: single sign-on, provisioning, admin roles and activity logs, built so the pilot can become a contract.
How does your rate compare to hiring in San Francisco?+
Built In puts the average base salary for a software engineer in San Francisco at about $181,000, before equity and benefits. Our published rate is $35 an hour, with a $5,000 minimum. There is no recruiting search and no employment overhead, and we can start within days. Most teams begin with a fixed-price two-week piece at $2,800, so you judge us on working code before committing to more.
Can you make our prototype ready for real customers?+
Yes, and it is a common place to start here. A prototype built fast for a demo usually needs the same things: model calls moved into queued, retried jobs, costs recorded per request, tests around the parts that change most, and deploys from CI. We read the code, send a written plan within a week, then take the most urgent piece as a fixed-price two-week job. The repository is yours throughout.
Should we run our own Kubernetes cluster?+
Usually not. Self-hosting starts to pay when your managed bill is mostly things you do not use, your workloads are steady rather than spiky, and someone is willing to own the control plane. We run our own on Hetzner, so we know what that job involves. If nobody on your side wants it, managed is cheaper in total even when the invoice is larger.
Do we need Kubernetes at all?+
Often not. Plenty of products are better served by a managed container service, a platform like Railway, or two virtual machines and a good deploy script. Kubernetes earns its place when you run several services, have steady traffic and have people to look after it. We will recommend the least infrastructure that does the job, and say so when that is less than you expected.
Which clouds do you work with?+
AWS most often, then Google Cloud, Azure and Hetzner. We work in whichever one you are already on, because moving clouds is rarely the cheapest fix for a cost or reliability problem. If we think a move is worth it, we will show you the case using your own bill before anyone migrates anything.
Can you cut our cloud bill without a migration?+
Usually, yes. Most of a bill that has grown unchecked is idle capacity, oversized instances, environments left running and data transfer nobody priced, and all of that is fixed where you already are. We will not promise a percentage before we have read the bill. After the first week we can tell you what is realistic and what it takes to get there.
Who is on call?+
Whoever the engagement says, in writing. While we run your infrastructure it can be us, with hours and response times agreed up front. If you are taking it in-house, the handover includes the runbooks, the alert routing and a rota your team can actually staff. We do not leave behind a pager that only we know how to answer.