Dotnet Architect/Senior Lead

As a .NET Technical Architect specializing in Copilot & Generative AI-Focus, your role will involve leading the design and implementation of modern enterprise applications with a strategic focus on AI-assisted development tools like GitHub Copilot and integration of Generative AI models into business applications. This is a unique opportunity to shape AI-first engineering practices while spearheading .NET modernization initiatives. Key Responsibilities: - Architect and design scalable, secure, and high-performance .NET applications using .NET 6/7/8, C#, ASP.NET Core, and Azure services. - Drive the integration and effective use of GitHub Copilot and similar AI coding assistants to accelerate development velocity and code quality. - Guide teams in adopting LLM-based solutions (e.g., OpenAI, Azure OpenAI, Hugging Face) to augment software functionality, such as chatbots, document summarization, and code generation. - Collaborate with product and innovation teams to explore opportunities for embedding Generative AI into customer-facing and internal tools. - Evaluate and implement secure design patterns for AI-enabled features, ensuring privacy, compliance, and responsible AI usage. - Lead PoCs and pilots for Copilot and Gen AI use cases, and scale successful initiatives across teams. - Coach developers and team leads in AI-assisted development methodologies, DevOps automation, and test-driven architecture. - Stay current with AI trends, Copilot enhancements, .NET ecosystem updates, and recommend relevant adoption strategies. Required Skills and Qualifications: - Bachelor's or master's degree in computer science, Engineering, or related field. - 10+ years of experience in .NET application architecture and development. - Strong knowledge of C#, .NET Core, ASP.NET Core, REST APIs, and Azure PaaS services. - Proven experience integrating or championing GitHub Copilot or similar developer productivity tools. - Hands-on experience with LLMs (OpenAI, Azure OpenAI, Google PaLM, etc.) and prompt engineering principles. - Solid grasp of cloud-native design, microservices architecture, event-driven systems, and DevOps pipelines. - Familiarity with AI ethics, data privacy, and governance in enterprise environments. Preferred Qualifications: - Experience building Gen AI-powered features like smart assistants, content generation, or semantic search. - Familiarity with Lang Chain, Semantic Kernel, Vector Databases (e.g., Pinecone, FAISS), or RAG architectures. - Prior experience in Agile, Scrum, or Scaled Agile (SAFe) environments. - Microsoft Certified: Azure Solutions Architect Expert or equivalent certification.,