key Responsibilities: Fine-tune and adapt open-source LLMs (e.g., LLaMA 4, Mistral and Bert) using NVIDIA GPU tools. Build AI agents using frameworks like LangChain, LangGraph, or AutoGen with structured workflows (memory, tools, retries, etc.). Implement hybrid LLM solutions using OpenAI/Claude APIs and open-source models. Develop APIs using FastAPI and containerize apps with Docker. Deploy, monitor, and scale AI solutions on AWS, Azure, or similar cloud providers. Collaborate with senior engineers to optimize performance and reliability of deployed systems. Requirements: Hands-on experience with LLM fine-tuning and NVIDIA GPU toolkits (CUDA). Familiarity with LangChain or similar agent frameworks. Experience developing APIs with FastAPI and deploying via Docker. Proficiency in using OpenAI/Anthropic APIs and building basic RAG pipelines. Solid foundation in Python, cloud deployment (AWS/Azure), and vector databases (e.g., FAISS, Pinecone). Nice to have: Exposure to tools like LangServe and Semantic Kernel Familiarity with CI/CD pipelines and monitoring tools (e.g., GitHub Actions, Prometheus). Contribution to open-source AI/ML projects. Soft Skills: · Strong communication skills - both verbal and written · Excellent problem-solving and debugging skills · Self-motivated with the ability to work independently and in a team · Comfortable working with stakeholders across different time zones Working Hours: General Shift: 1:30 PM to 11:30 PM IST Flexibility to extend hours based on critical deployments or support needs