AI/ML Engineer (LLM & RAG)

About the Role We are looking for an experienced AI/ML Engineer to design, build, and scale enterprise-grade Generative AI solutions. The ideal candidate should have strong expertise in Large Language Models, Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, and modern AI orchestration frameworks. Responsibilities Design and develop scalable LLM-powered applications. Build production-ready Retrieval-Augmented Generation (RAG) systems. Design document ingestion, indexing, and retrieval pipelines. Integrate and optimize Vector Databases for high-performance semantic search. Develop AI agents and workflows using LangChain and/or LlamaIndex. Implement prompt engineering strategies and prompt optimization techniques. Fine-tune open-source LLMs where appropriate. Evaluate model performance using standard AI evaluation metrics. Optimize latency, token usage, and overall system cost. Build REST APIs and microservices using Python. Deploy AI solutions to cloud environments. Collaborate with product, engineering, and data teams to deliver AI-driven products. Stay up to date with the latest advancements in Generative AI and LLM technologies. Required Skills 36 years of experience in AI/ML or NLP development. Strong expertise with Large Language Models: OpenAI, Claude, Gemini Open-source LLMs (Llama, Mistral, Qwen, etc.) Strong experience with Retrieval-Augmented Generation (RAG) Hands-on experience with Vector Databases: Pinecone, Weaviate, Chroma, FAISS Strong Prompt Engineering skills Experience with LangChain and/or LlamaIndex Experience in fine-tuning and evaluating LLMs Strong Python programming skills Experience with FastAPI or Flask Knowledge of embeddings, semantic search, reranking, and hybrid search Familiarity with Git and CI/CD workflows Preferred Skills Hugging Face ecosystem vLLM, Ollama, or TensorRT-LLM Docker and Kubernetes Redis or Elasticsearch GraphRAG and Knowledge Graphs AWS, Azure, or Google Cloud Monitoring and observability tools (LangSmith, Phoenix, Weights & Biases) Preferred Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Contributions to open-source AI projects or an active GitHub profile. Experience deploying enterprise-grade AI applications. Benefits: Flexible schedule Work from home .