Ecommerce development in San Francisco
San Francisco has a steady stream of hardware startups selling a device and a subscription together: a sensor, a wearable, a home gadget, with a monthly plan that makes the numbers work. Their ecommerce is harder than a normal store. Preorders take money before stock exists, the subscription has to start when the device arrives rather than when it ships, and customers expect to pause, swap or cancel a plan online without writing to support.
We build commerce that ties those pieces together. The storefront can be Shopify or custom. Behind it, orders, shipments, device activation and subscription entitlements sit in one model, so support can see why a customer was charged and a cancelled plan actually stops billing. Preorder and backorder states are explicit, and customers see an honest date.
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.
The ERP updates overnight, the store sells all day, and by morning the two do not match. We build the sync as a queue with retries and reconciliation, decide which system wins for each field, and alert on drift before a customer buys stock you do not have.
Or checkout slows until people give up. We cache what can be cached at the edge, keep live stock checks off the browsing path, load-test the shape of a real launch rather than a steady trickle, and queue anything that cannot scale.
Bundles, B2B price lists, subscriptions, delivery rules by postcode. We build it as a custom Shopify app or with Shopify Functions and checkout extensions so it survives platform updates, or tell you when you have outgrown the theme altogether.
Payment webhooks can arrive twice, late or out of order, and the handler trusts every one. We make order state follow the provider's record, process Stripe and Razorpay events idempotently, and reconcile daily so a mismatch is a report, not a complaint.
An hourly sync with a third-party system reachable only through its API, with values normalised at the boundary so unchanged records stop looking changed.
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.
Have you built a store like ours?+
We build stores from the parts of commerce that usually go wrong, and those are what we work on every day: syncing with a third-party system that only speaks through its API, handling webhooks that arrive twice, and background jobs that must not lose or repeat work. On a call we will walk you through how that applies to your store.
Shopify, headless, or fully custom?+
Start with Shopify if a theme and a few apps cover you; that is cheaper than anything we would build. Go headless when the storefront must do things a theme cannot, or share a front end with other products. Build on Medusa or commercetools when the catalogue, pricing or order flow is genuinely unusual. Most stores never need the third option, and we will say so.
Can you connect our ERP or warehouse system?+
Usually, if it has an API or can export files on a schedule. We start by agreeing which system owns each field, such as stock, price and order status, because most sync bugs come from two systems both believing they are the source of truth. Then we build the sync with retries, a log of every change, and a daily reconciliation report.
Which payment providers do you work with?+
Stripe, Razorpay, and Shopify Payments when the store runs on Shopify. Choose the one that suits your markets and fees; we earn nothing from any of them. The work that matters is the same for all three: treat the provider as the record of what was paid, handle every webhook idempotently, and test refunds and partial captures, not only the happy path.
How do you prepare for a sale or a launch?+
We load-test the whole journey, from landing page to paid order, at the traffic you expect and beyond it. We find what breaks first, which is usually a third-party script, an uncached page or the stock check, and fix it before the day. During the sale itself, the engineer who did that work is watching the dashboards with you.