Key Responsibilities :

- Design, develop, and deploy AI-powered applications and enterprise solutions.

- Build scalable full-stack applications using .NET, React/Angular, Node.js, and Python.

- Integrate and deploy LLM-based solutions using AWS Bedrock, Azure OpenAI, or Google Vertex AI.

- Develop RAG pipelines, AI agents, and agentic workflows using modern GenAI frameworks.

- Integrate OpenAI, Anthropic, and open-source LLMs into production applications.

- Design and implement solutions using vector databases, embeddings, and prompt engineering.

- Build and deploy AI/ML models using PyTorch, TensorFlow, and related frameworks.

- Develop scalable microservices, APIs, FaaS/PaaS solutions, and cloud-native applications.

- Implement AI evaluation, observability, monitoring, and performance optimization.

- Work with LangChain, LangGraph, LangSmith, LangFuse, or similar AI frameworks.

- Implement CI/CD, DevSecOps, and SRE practices for AI and software workloads.

- Collaborate with product, engineering, data science, and architecture teams to deliver production-ready solutions.

- Troubleshoot, optimize, and continuously improve AI applications for scalability, reliability, latency, and cost.

Mandatory Skills :

- 6-9 years of software engineering experience.

- Strong .NET development experience mandatory.

- Full-stack development using React / Angular / Node.js.

- Strong Python programming.

- Hands-on experience with AWS / Azure / GCP.

- 3+ years of hands-on AI/ML and Generative AI experience.

- Experience with AWS Bedrock / Azure OpenAI / Vertex AI.

- LLM integration with OpenAI, Anthropic, or open-source models.

- RAG, Prompt Engineering, Vector Databases.

- AI Agents / Agentic AI.

- LangChain / LangGraph.

- Microservices and API development.

- SQL / NoSQL databases.

Preferred Skills :

- PyTorch / TensorFlow.

- FaaS / PaaS and cloud-native architecture.

- DevSecOps / SRE.

- GitHub / SonarQube / MLflow.

- AI evaluation and observability.

- LangSmith / LangFuse.

- Experience taking AI solutions from POC to production.

Ideal Candidate :

- A hands-on engineering professional who combines strong .NET/full-stack development with GenAI, Agentic AI, LLM, and cloud expertise, and can independently contribute across the complete AI product lifecycle from architecture and experimentation to production deployment, monitoring, and continuous optimization.