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Atomic - Remote Jobs is seeking a seasoned full-stack engineer to extend and own end-to-end features for a live workflow product. You will work on the server side (Azure SQL, API), database migrations and React/TypeScript UI, guided by AI-assisted specs.
Collaboration with the product manager and lead developer occurs in a fast-paced two-week sprint cadence, with a focus on delivering four to five features per sprint.
Our client is a remote product studio that builds MVPs and custom software for startups and companies past the idea stage. Clients hire them for a fixed-scope MVP or for a product team billed by the two-week sprint, and the whole team uses AI coding tools every day.
Our client is a remote product studio that builds MVPs and custom software for startups and companies past the idea stage. Clients hire them for a fixed-scope MVP or for a product team billed by the two-week sprint, and the whole team uses AI coding tools every day.
They've been at it since 2020 and were profitable in 2025, with a 30% net margin. After building their own AI systems, they tripled monthly revenue with the same team size. Clients rate them 4.9 out of 5 in verified reviews, and the startups they build for have raised more than $25M in venture funding.
You'll join the team building workflow software for one of the studio's clients: a live product that needs new workflow features while the existing ones keep running. The client's own engineers commit to the same repo, so every new table, permission and workflow goes in next to code someone else is changing. The weight is on the server side, from the SQL database on Azure up through the API, and you also build the React and TypeScript screens that sit on top. AI coding tools draft most of the specs, tests and migrations. You direct them, read every diff line by line, and answer for what merges. If you'd rather write most of the code by hand, this probably isn't the right seat. You report to the studio's leadership and work day to day with the lead developer and the product manager, who sets the acceptance criteria for each sprint. Success means delivering four to five features per two-week sprint, each verified before merge, and owning one area end to end (such as the task engine or the legacy migration) without breaking a live feature.