- Design and develop enterprise-grade Generative AI and NLP solutions using Large Language Models (LLMs).

- Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and semantic search techniques.

- Develop production-ready AI applications leveraging frameworks such as LangChain, LangGraph, and LlamaIndex.

- Implement Agentic AI and multi-agent workflows to automate complex business processes.

- Optimize AI performance using advanced RAG techniques such as document chunking, hybrid retrieval, reranking, query rewriting, and feedback loops.

- Integrate structured knowledge bases and knowledge graphs to improve contextual understanding and response accuracy.

- Deploy and manage AI solutions on AWS Bedrock, SageMaker, Azure OpenAI, Azure ML Studio, or Azure AI Foundry.

- Collaborate with product, cloud, software, and data engineering teams to design scalable, secure, and production-ready AI solutions.

- Implement MLOps best practices, including model deployment, monitoring, logging, and lifecycle management.

- Continuously evaluate and improve AI model performance, scalability, and reliability while minimizing hallucinations.

Preferred Candidate Profile :

- 8 years of software development, AI/ML, or Generative AI experience.

- Strong proficiency in Python and hands-on experience with Large Language Models (LLMs) and Generative AI.

- Proven experience designing and implementing RAG-based applications.

- Hands-on expertise with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.

- Experience with vector databases such as Pinecone, FAISS, ChromaDB, Weaviate, or Milvus.

- Good understanding of Agentic AI, semantic search, embeddings, and prompt engineering.

- Experience deploying AI solutions on AWS Bedrock, SageMaker, Azure OpenAI, or Azure AI Foundry.

- Familiarity with MLOps, Docker, Kubernetes, CI/CD, and AI model monitoring.

- Strong problem-solving, communication, and stakeholder management skills.

- Experience working in enterprise-scale AI projects is highly preferred.