Job Description & Details
This is a hands-on .NET engineering role focused on building out investment lifecycle solutions with an explicit emphasis on AI-assisted development. You will be sitting at the intersection of traditional enterprise architecture and modern AI tooling, meaning you need to ship clean C# code while figuring out how to actually use AI to speed up velocity without breaking production.
What You'll Actually Be Doing
Your day-to-day will involve building and maintaining web UIs, writing REST APIs, and keeping production systems stable. You won't just be writing code the traditional way; you'll be actively applying approved AI tools and prompt engineering patterns to validate code and optimize workflows. Expect to collaborate heavily with product, security, and architecture teams to design secure, scalable features, while also mentoring junior engineers on your team and writing technical specs.
The Core Tech Stack
You need to bring a solid foundation in C#, .NET, and SQL Server, backed by 3 to 5 years of relational database experience. Since this role requires you to integrate AI workflows, familiarity with API integration, prompt engineering, and modern single-page application frameworks like Angular is critical. You'll also need to be comfortable using Git and Jira for day-to-day tracking and version control in an enterprise environment.
Interview Expectations
When you talk to the engineering managers, be prepared to walk them through a time you debugged a complex performance bottleneck in a full-stack .NET application under pressure. They want to see how you systematically isolate database versus application layer issues. You should also expect a deep dive into how you personally use AI tools in your development workflow; they aren't looking for buzzwords here, but rather a practical understanding of how you maintain code quality and handle data privacy when leaning on LLMs.
Application Advice
Make sure your resume clearly highlights your hands-on backend experience with C# and .NET alongside specific mentions of REST API integrations and SQL Server tuning. Don't just list AI as a skill; weave it into your bullet points by describing how you have used AI tools or prompt engineering to accelerate your delivery cycles or validate code. Keeping these exact terms visible will help your resume clear the ATS filters before a human engineer actually reviews your architecture background.