Key Responsibilities

• Design, develop, and deploy AI/ML and Generative AI applications
• Build applications using Large Language Models (LLMs) such as GPT, Claude, Llama, or Gemini
• Develop Retrieval-Augmented Generation (RAG) pipelines for enterprise AI solutions
• Fine-tune and optimize foundation models using frameworks like Hugging Face
• Create AI agents and workflow automation using frameworks such as LangChain, LangGraph, CrewAI, or AutoGen
• Develop REST APIs and microservices for AI model integration
• Work with vector databases such as Pinecone, FAISS, Weaviate, ChromaDB, or Milvus
• Build prompt engineering strategies to improve AI model performance
• Deploy AI solutions on cloud platforms (AWS, Azure, or GCP)
• Implement MLOps practices for model deployment, monitoring, and versioning
• Collaborate with product managers, data scientists, and software engineers to deliver AI-driven solutions
• Optimize AI models for scalability, latency, and cost efficiency
• Stay updated with the latest advancements in AI, LLMs, and Generative AI

Requirements

• Experience with AI/ML development and production deployment
• Knowledge of cloud platforms (AWS, Azure, or GCP)
• Hands-on experience with LLMs and generative AI techniques
• Strong collaboration with cross-functional teams

Skills Required