Job Description :

We are looking for an experienced .NET Full Stack Developer AI/GenAI to join our team and work with a leading MNC on modern, cloud-native applications powered by AI/ML and Generative AI technologies.

The ideal candidate will have strong hands-on expertise in C#, .NET, Angular/React, Azure, and modern AI/ML technologies, along with experience building GenAI, RAG, and agentic applications. The candidate should be comfortable working across the full software development lifecycle and applying modern engineering practices to deliver scalable, secure, and high-quality products.

Key Responsibilities :

- Design, develop, test, and maintain scalable full-stack applications using C#, .NET, Angular/React, and Node.js.

- Build and integrate AI/ML and Generative AI solutions into enterprise applications.

- Develop LLM-powered applications, AI agents, assistants, and agentic workflows.

- Design and implement RAG pipelines, prompt engineering workflows, vector search, and AI evaluation frameworks.

- Integrate LLMs from providers such as OpenAI, Anthropic, and open-source models.

- Work with AI/ML frameworks and technologies including PyTorch, TensorFlow, LangChain, and LangGraph.

- Design and implement scalable cloud-native applications using Azure, AWS, or GCP.

- Work with cloud AI/ML services such as Azure OpenAI, AWS Bedrock, or Google Vertex AI.

- Develop microservices and serverless applications using FaaS, PaaS, and containerized architectures.

- Work with SQL and NoSQL databases and design efficient data models and data access layers.

- Implement infrastructure-as-code and follow cost-aware engineering and FinOps practices.

- Develop robust unit and integration tests and ensure high code quality through automated testing and code analysis.

- Apply OOP/OOD, data structures, algorithms, and software engineering best practices.

- Create and interpret Business Context Diagrams, sequence diagrams, activity diagrams, state diagrams, entity-relationship diagrams, and data flow diagrams.

- Use AI-augmented and spec-driven development practices to accelerate software delivery.

- Collaborate with product, engineering, data science, and business teams to understand requirements and deliver solutions.

- Apply modern engineering methodologies including XP, Lean, DevSecOps, and SRE.

- Monitor application performance, reliability, security, and operational health.

- Participate in code reviews, technical design discussions, and continuous improvement initiatives.

Required Skills & Qualifications :

- Bachelor's degree in Computer Science, Software Engineering, Data Science, Machine Learning, or a related discipline. Relevant professional experience will also be considered.

- 6-9 years of overall software development experience, with strong hands-on experience in most of the following :

1. C# / .NET

2. Angular / React

3. Node.js

4. Python

5. Java

6. SQL / NoSQL

7. PyTorch

8. TensorFlow

9. LangChain

10. LangGraph

11. Unit testing frameworks

- 3+ years of experience developing AI/ML and agentic applications.

- Hands-on experience with Generative AI and LLM-based applications, including :

1. LLM integration

2. RAG pipelines

3. Prompt engineering

4. Vector databases

5. Model/application evaluation

6. AI agent orchestration

- Experience working with LLM providers such as OpenAI, Anthropic, or open-source models.

- 3+ years of cloud-native engineering experience using Azure, AWS, or GCP.

- Experience with cloud AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI.

- Strong understanding of microservices, FaaS, PaaS, and cloud-native architectures.

- Experience with Infrastructure as Code (IaC) and cost optimization/FinOps practices.

- Strong understanding of OOP/OOD, data structures, algorithms, system design, and code instrumentation.

Tools & Engineering Practices :

- Experience with the following methodologies and tools is preferred :

1. XP / Extreme Programming

2. Lean

3. DevSecOps

4. SRE

5. Azure DevOps (ADO)

6. GitHub

7. SonarQube

8. MLflow

9. LangFuse

10. LangSmith

11. Multi-agent orchestration frameworks