Custom software development in Seattle
Seattle's global health and research organisations collect data in places with poor connectivity, on shared devices, in several languages, and often about people whose privacy matters more than usual. The software available off the shelf tends to assume a good connection and a single language, and it rarely fits a study's actual workflow.
We build custom tools for that kind of work: forms that work offline and sync when a connection appears, data checked for obvious errors at the point of entry, interfaces translated properly, and access controls that follow the study's rules about who may see what. Data is minimised at collection, and every change is recorded. We start with the workflow the field team uses today, including its paper steps, and build the smallest version that improves it.
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.
Approvals, schedules or stock, tracked in a shared file with colour codes only one person understands. We turn it into an application with proper records, permissions and history, so you can see who changed what and when, and nobody works from an old copy.
Staff copy data from one system into another by hand, and the two slowly drift apart. We connect them through their APIs, clean up the data where it crosses over, and alert someone when a sync fails instead of letting it fail quietly.
The numbers exist, spread across exports and inboxes, and someone assembles a report by hand every Monday. We pull them into one place, build the dashboard the people making decisions will actually open, and check it is current rather than trusting the job that feeds it.
A legacy application still runs the business and every change to it is a risk. We map what it really does, move it piece by piece onto something maintainable, and keep both running until the last piece has landed. No weekend cut-over.
A facilities operations platform for a healthcare estate, built so supervisors can see what is overdue and what keeps coming back without exporting spreadsheets by hand.
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.
Why not buy an off-the-shelf tool?+
Often you should, and we will tell you when. If a product already does most of what you need, configuring it is cheaper than building. Custom software earns its cost when the process is how you compete, when you pay for several tools to do one job badly, or when the workarounds cost more staff time than the software would.
Can you work with the systems we already have?+
That is usually the job. Most internal tools are valuable because of what they connect to: an ERP, a work-order system, a CRM, a finance package. If it has an API, we integrate with it. If all it offers is a nightly export, we can work with that too, and we will tell you how fresh the data can honestly be.
How do you find out what we actually need?+
By talking to the people who do the work, not only the people who asked for the tool. We watch the spreadsheet being used, collect the edge cases everyone handles from memory, and write the process down before we build anything. The first release covers the core of it; the exceptions follow once people are using it.
What happens to our old data?+
It comes with you. We migrate it, check the counts and totals against the source, and keep the old system or spreadsheet readable until your team is confident nothing was lost. Where the old data is inconsistent, we show you the records that do not fit rather than quietly guessing what they meant.
Who looks after it once it is live?+
You choose. We can stay on at our hourly rate for changes and fixes, or hand it to your own team with runbooks, architecture notes and a recorded walkthrough. Internal tools change as the business changes, so we build them to be changed by someone other than us.