C# Dotnet AI Developer

Sr Backend Software Engineer - AI (Artificial Intelligence)

Duration: 12 months (Likely to extend)

The Senior Backend Software Engineer is a leadership role on the platform engineering team, responsible for guiding architecture, prototyping, and delivering solutions in close collaboration with the CTO and other engineers. This role will require both designing distributed systems and serving as a champion for AI-enabled software engineering practices across the organization.

Environment snapshot:

C#/.NET 8 microservices → Docker → Kubernetes on Azure; async messaging (AMQP/Service Bus); Cosmos DB; heavy AI-assisted development culture.

Must-have checklist:

• Expert C# with modern.NET (API controllers thin; business logic in services)
• Containers & K8s: Docker, Helm, deploy/debug on AKS
• Asynchronous, durable messaging: AMQP / Azure Service Bus
• Distributed systems at scale: horizontal elasticity, fault tolerance, perf/load testing
• Cosmos DB in production (schema design, RU/perf tradeoffs)
• CI/CD in Azure (e.g., Azure Pipelines) and "own what you ship" ops mindset
• Daily use of AI coding tools (Copilot/test gen/review) with concrete productivity examples

Strong plus:

• Semantic Kernel (C# or partnering with Python) / agentic patterns
• RAG familiarity, Azure Cognitive Search, Azure Functions
• EF, MSTest/xUnit, deep K8s troubleshooting, profiling across service + DB

Responsibilities and Duties:

• Analyze, design, and develop distributed systems on Azure Cloud.
• Leverage AI development tools (e.g., GitHub Copilot, Azure AI integrations, AI-driven testing frameworks) to increase productivity, reduce errors, and accelerate delivery.
• Promote AI best practices within the engineering team—educating peers on how to effectively use AI copilots, RAG-enabled knowledge bases, and automated code review assistants.
• Build and maintain proof-of-concepts using AI-assisted approaches to explore new architectures and solutions.
• Drive automation across development and operations through AI-enhanced workflows.
• Evaluate existing code and coach engineers in applying both traditional best practices and AI-assisted improvements in design patterns, testing, and maintainability.
• Collaborate cross-functionally with data scientists, business users, and other engineers to integrate AI into backend processes and product features.
• Provide ongoing maintenance, support, and enhancements in existing systems and platforms.
• Ensure solutions are secure, scalable, and meet performance requirements in high-load environments.

Qualifications:

• Expert-level experience with backend development in C#, Docker, Azure, and distributed systems.
• Strong understanding of messaging protocols (AMQP, gRPC, etc.) and experience with Service Bus and durable messaging patterns.
• Proven track record of using AI tools in day-to-day development—demonstrated ability to write, review, test, and optimize code with AI copilots and automation platforms.
• Experience incorporating AI into CI/CD pipelines, test automation, and developer productivity workflows.
• Familiarity with Azure CosmosDB, Azure Search, Azure Functions, Kubernetes, and big-data platforms.
• Strong DevOps focus and experience building and deploying infrastructure with technologies like Azure Pipelines, Helm, and Docker.
• Experience with test-driven development, automated testing frameworks, and performance/load testing.
• Agile/Scrum experience with a highly collaborative mindset.
• Excellent verbal and written communication skills.
• Experience with REST, Entity Framework, MSTest, and performance testing solutions.

AI Coding Tool Proficiency:

• IDE-Native Assistants like GitHub Copilot or JetBrains AI Assistant
• AI IDEs / Agentic Development Environments - ChatGPT Codex for engineering tasks such as PRs, test generation, or repo Q&A
• Model-Centric Coding Assistants - Claude (Anthropic) for code reasoning or IDE integrations