Role Overview :

- Design, develop, and maintain enterprise applications using the .NET ecosystem.

- Build scalable full-stack applications and APIs using Microsoft technologies.

- Integrate AI capabilities into existing and new applications using Azure AI services.

- Develop and operationalize AI-powered search, RAG solutions, and assisted/autonomous agents.

- Work closely with product, architecture, and business teams to deliver scalable enterprise solutions.

Experience :

- 7 to 10 years of overall Full Stack development experience.

- Strong hands-on experience in the .NET ecosystem.

- 2 - 4 years of experience in AI Engineering / Generative AI.

- Strong experience with Microsoft Azure technologies.

Core Technical Skills - .NET :

- Strong expertise in C# and .NET / .NET Core.

- Experience developing REST APIs and microservices.

- Strong understanding of Object-Oriented Programming and design patterns.

- Experience with ASP.NET Core / Web API.

- Experience with SQL Server and database development.

- Strong understanding of Entity Framework / ORM.

- Experience with HTML, CSS, JavaScript/TypeScript.

- Exposure to modern frontend frameworks such as React or Angular.

- Experience with Azure App Service, Azure DevOps and CI/CD pipelines.

- Understanding of Azure cloud architecture, including:

1. Azure App Service

2. Azure Functions

3. Azure Key Vault

4. Azure Monitor

5. Azure Kubernetes Service (AKS)

- Experience in application performance tuning, scalability and troubleshooting.

- Strong understanding of secure application development and API integration.

Must Have :

- Hands-on experience with Azure OpenAI Service.

- Experience with LLM integration and prompt engineering.

- Experience with embeddings and vector-based search.

- Strong experience with Azure AI Search, including: Vector Search, Hybrid Search, Reranking.

- Experience developing Retrieval-Augmented Generation (RAG) pipelines.

- Experience integrating AI capabilities into .NET applications.

- Understanding of AI application performance optimization, including:

1. Token optimization

2. Latency optimization

3. Embedding optimization

4. Caching

Good to Have :

- Experience with Azure Machine Learning.

- Experience with Microsoft Power Automate / Power Platform.

- Experience with Microsoft Graph API and M365 integration.

- Exposure to Microsoft Foundry.

- Experience developing AI agents / agentic workflows.