Ecommerce development in Seattle
Seattle brands often sell in two places at once: on Amazon's marketplace, where the shoppers already are, and on their own store, where the margin and the customer relationship are. Running both from separate spreadsheets means stock that sells twice, prices that drift apart and customer data split in two.
We build the connective tissue between channels. One inventory record feeds your own store and the marketplace listing, orders from both flow into one fulfilment queue, and pricing rules live in one place. The storefront itself can be Shopify or custom. What matters is that the numbers agree, finance can reconcile every channel against what was actually paid out, and a sold-out product stops selling everywhere at once. Returns and refunds are tracked per channel too, since each one settles differently.
Seattle's software market was shaped by Amazon and Microsoft, and by the cloud platforms they run. Many of the region's startups were founded by people who left one or the other, and they cluster in cloud infrastructure, developer tools, enterprise software and, increasingly, AI. Around them sit life sciences and global health organisations, retail and outdoor brands, and a long tail of companies whose entire estate lives in AWS or Azure. Buyers here have usually run services at scale themselves, and it shows in what they ask for.
The practical effect is more rigour and less explaining. A Seattle buyer expects a written design before code, with the alternatives considered and the reasons one was chosen. They count metrics, alarms and a runbook as part of done, not a later phase, and they want trade-offs stated plainly. Most already have a cloud agreement and committed spend on AWS or Azure, so the job is usually to make that estate tidier, cheaper and better understood. The other common pattern is the founder who left a large company and misses its internal platforms, because at a startup nobody has built them yet.
Built In puts the average base salary for a software engineer in Seattle at around $149,000, and the large employers add stock on top, which is what a startup is really competing against. A senior search can run for months, and the work that waits is often the most concrete on the roadmap: a service split out of a monolith, a migration, a cloud clean-up, a model moved from a notebook into production. Each has a clear finish line, which makes it a good fit for a small team that writes the design first and the runbook as it goes.
We work from Bengaluru with four hours of live overlap every working day, placed across your morning in Seattle. Stand-ups and design reviews 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 each day starts with a written record of what changed.
We fit best on work with a clear finish line: a new service, a migration, a cloud clean-up or a model moved into production. We add senior capacity within days while a req stays open, starting 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 Seattle teams.
How do you work with teams in Seattle?+
From Bengaluru, with four hours of live overlap every working day placed across your Seattle morning. Stand-ups and design reviews happen in that window, and you talk to the engineer who writes the code. We work in your Slack, your GitHub and your Linear. Designs are reviewed before code, and runbooks and architecture notes are written as we go, so the record lives where your team already works.
Do you work with teams already running on AWS or Azure?+
Yes, and in Seattle that is most teams. We work inside the estate you have: hand-built resources imported into Terraform, serverless functions made idempotent and traced end to end, cloud costs broken down per customer and feature, and AI features built on Bedrock or Azure OpenAI through the access your agreement already covers. The aim is an account that is tidier, cheaper and easier to explain, on the cloud you already pay for.
How does your rate compare to hiring in Seattle?+
Built In puts the average base salary for a software engineer in Seattle at about $149,000, before stock, benefits and recruiting fees. 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. The usual first step is a fixed-price two-week piece at $2,800, so you judge us on shipped work before committing to more.
What do the first two weeks look like?+
You share the context, and within two days you have a 30-minute call with the engineer who would do the work. Within a week you get a written plan: the options, the one we recommend and why, and how it rolls out. Then comes a fixed-price two-week piece, built in your repository from the first commit, with the design reviewed before code and the runbook written as it goes.
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.