Senior .NET / Azure Developer

We are an IT services company based out of San Francisco, USA. ​​We build and acquire expert engineering teams to help our clients meet their business needs and solve their operational challenges.

We are looking for a Senior Software Engineer for long-term contract work to join one of our client’s Development Product Teams. This is a hands-on engineering role. You will write the code, review it, deploy it, and be on the hook when it misbehaves. There is no layer between you and production, and no layer between you and the people who depend on the platform.

This position may require working between the hours 12:00 PM to 8:00 PM Kyiv time. 

Tech Stack: 

• Backend: C# / .NET (ASP.NET Core Web API), Entity Framework, xUnit, REST APIs
• Azure: App Service and deployment slots, Azure SQL, Redis, Key Vault, Functions/WebJobs, Service Bus, Event Grid, Application Insights / Log Analytics, Azure DevOps pipelines
• Edge: Cloudflare (WAF, Workers, cache and redirect rules)
• Integrations: Salesforce (REST and SOAP APIs, OAuth, Connected Apps), OIDC-based member identity, learning and event platforms
• AI & Developer Tooling: GitHub Copilot, ChatGPT, Claude, or similar AI-assisted development tools

Requirements: 

• 8+ years building and running production C#/.NET web applications and APIs, including ownership of what you shipped.
• Strong, current Azure experience as a developer who operates their own environments: App Service and slots, Azure SQL, Key Vault, managed identities, and diagnosing problems from logs and metrics rather than guesses.
• Comfort in a small team with a wide surface area: you can pick up unfamiliar code, work without a spec, and ask the sharp question early.
• Must have experience applying AI within development. More detailed experience with AI-Native development and AIDLC preferred.

Would be Preferred:

• Azure DevOps (or comparable) pipelines — you have built and fixed CI/CD, not just pushed the button.
• Integration work against third-party SaaS APIs — OAuth flows, rate limits, sandbox data, and the failure modes that only appear in production.
• Salesforce platform integration experience (Connected Apps, client-credentials OAuth, staging test data).
• Automated testing as a habit, not a phase: unit, integration, and end-to-end, and the judgement to know which one a given risk deserves.