Job Description & Details
This 12-month contract is not your average enterprise .NET gig; you will be knee-deep in building cloud-native, AI-enabled systems using both Azure and GCP. If you enjoy the blend of solid backend architecture and bleeding-edge GenAI integration without getting bogged down in AWS, this role offers a great runway to lead delivery.
What You'll Actually Be Doing
You will spend your days leading the full SDLC for enterprise applications, running code reviews, and mentoring other engineers while writing clean C#, Python, and React or Blazor code. Expect to architect REST APIs, manage microservices through platforms like Apigee, and directly implement GenAI features like RAG pipelines, vector search, and LLM integrations. Much of your time will also be dedicated to optimizing deployments across Azure App Services, Azure SQL, and Google Cloud BigQuery while keeping a close eye on cost, security, and scalability.
The Core Tech Stack
Your bread and butter here will be .NET Core, C#, Python, and React or Blazor, underpinned by a deep understanding of SOLID principles and design patterns. Because this environment completely bypasses AWS, you need rock-solid, hands-on experience in both Azure and Google Cloud Platform engineering. Knowing how to tie together Azure DevOps, Apigee API management, and GCP data services like BigQuery is non-negotiable if you want to keep these distributed systems running smoothly.
Interview Expectations
You will likely be asked to explain how you would design a low-latency RAG pipeline that handles token limits and securely queries internal vector databases stored in GCP or Azure. The interviewer is secretly testing whether you understand the actual operational costs and failure modes of GenAI at scale, rather than just knowing how to call an OpenAI API. They will also drill into your microservices troubleshooting strategy, looking for a methodical breakdown of how you isolate bottlenecks across multi-cloud network boundaries and API gateways.
Application Advice
To make it past the ATS, ensure your resume explicitly highlights dual-cloud proficiency in both Azure and GCP, as general 'cloud experience' won't cut it here. Front-load your experience with specific keywords from the description like ASP.NET Core, Python, React, vector search, RAG, and Apigee. Frame your past contract work around measurable outcomes, specifically mentioning how you optimized cloud costs or led technical mentorship for engineering teams.