Job Description & Details
This is a heavy-hitting .NET engineering gig nested squarely inside the high-stakes financial domain, specifically touching broker-dealer workflows. You aren't just writing standard enterprise code here; you are modernizing core transaction engines while heavily leaning into generative AI-assisted development across the entire SDLC.
What You'll Actually Be Doing
Expect to spend your days designing and modernizing resilient, distributed .NET services and event-driven pipelines. You will be knee-deep in high-volume transaction processing, utilizing tools like Kafka and IBM MQ to keep data moving smoothly. A major chunk of your routine will also involve leveraging GenAI coding assistants, agentic workflows, and prompt engineering to accelerate your daily output—from scaffolding and refactoring to automated testing and documentation—while still owning the ultimate correctness of the architecture.
The Core Tech Stack
To survive and thrive here, you need deep, battle-tested expertise in modern .NET, message streaming via Apache Kafka, and cloud-native deployments utilizing Docker and Kubernetes (on GCP or AWS). Because this is financial tech, familiarity with Twelve-Factor App methodologies, robust observability tools like Splunk, and distributed data stores like MongoDB, PostgreSQL, or Aerospike are non-negotiable. Add in your practical fluency with AI tools like GitHub Copilot or Claude Code, and you'll have the exact toolkit they're looking for.
Interview Expectations
Expect the hiring team to grill you on distributed systems resilience, failure recovery, and how you handle partition management or consumer lag in high-throughput Kafka architectures. They want to know how you balance speed with safety when using GenAI coding tools, so be prepared to walk through concrete examples of how you prompt, test, and validate AI-generated code to ensure it meets strict enterprise security and performance standards without introducing regressions.
Application Advice
When updating your resume for this role, make sure you don't just list .NET and C#; explicitly highlight your production experience with event-driven architectures, message brokers, and cloud-native microservices. Weave in specific keywords from the job description such as Twelve-Factor App, Kafka, Kubernetes, and any hands-on AI-assisted tooling like GitHub Copilot or agentic workflows so you easily clear the ATS filters and grab the attention of the engineering manager.