Key Responsibilities:

- Design, develop, and deploy production-grade Generative AI and Agentic AI solutions.
- Build intelligent AI agents and workflows using LangChain, LangGraph, and MCP.
- Design and implement RAG-based applications using appropriate retrieval and augmentation techniques.
- Work with Vector Databases to build scalable semantic search and knowledge retrieval systems.
- Develop robust backend services and APIs using Python and FastAPI.
- Design and implement scalable microservices-based AI applications.
- Deploy and manage AI applications using Docker and Kubernetes.
- Leverage Azure and GCP services for developing, deploying, and scaling AI solutions.
- Collaborate with product managers, data scientists, software engineers, and other stakeholders to translate business requirements into technical solutions.
- Optimize AI applications for performance, scalability, reliability, and cost efficiency.
- Ensure solutions follow best practices for security, testing, monitoring,



and production deployment.
- Stay updated with emerging developments in Generative AI, Agentic AI, LLMs, AI frameworks, and cloud technologies.

Required Skills & Qualifications:

- Robust hands-on experience in Generative AI and Agentic AI.
- Excellent proficiency in Python.
- Hands-on experience with:
- LangChain
- LangGraph
- MCP (Model Context Protocol)
- RAG (Retrieval-Augmented Generation)

5.

Vector

Databases

- Strong understanding of LLMs and enterprise AI application development.
- Experience with Azure and GCP cloud platforms.
- Hands-on experience with FastAPI, Docker, and Kubernetes.
- Strong understanding of microservices architecture.
- Experience building and deploying production-grade enterprise AI solutions.
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration skills.

📌 Senior AI Engineer - Generative AI/Agentic AI Solutions (India)
🏢 MAGIC BLOOMS MEDIA PRIVATE
📍 India