We are looking for an AI Engineer with hands-on experience in Large Language Models (LLMs), Generative AI, and modern AI frameworks. The ideal candidate will design, develop, and deploy intelligent AI applications powered by state-of-the-art language models. You will work closely with product, engineering, and data teams to build scalable AI solutions that solve real-world business problems. Key Responsibilities Design, develop, and deploy LLM-powered applications and AI agents. Build Retrieval-Augmented Generation (RAG) pipelines using vector databases. Develop prompt engineering strategies and optimize model performance. Integrate LLM APIs (OpenAI, Anthropic, Google Gemini, Azure OpenAI, etc.) into applications. Fine-tune and evaluate open-source LLMs where applicable. Develop AI workflows using frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or similar. Build REST APIs and microservices for AI applications. Implement AI guardrails, content moderation, and security best practices. Optimize inference performance, latency, and operational costs. Collaborate with cross-functional teams to deliver production-ready AI solutions. Stay current with emerging AI technologies, research, and industry trends. Required Skills Strong proficiency in Python. Experience with Large Language Models and Generative AI. Hands-on experience with LangChain, LlamaIndex, CrewAI, AutoGen, or similar frameworks. Knowledge of RAG architectures and vector databases (Pinecone, Weaviate, Chroma, FAISS, Milvus, etc.). Experience with embedding models and semantic search. Familiarity with OpenAI, Anthropic, Gemini, Azure OpenAI, or open-source LLMs (Llama, Mistral, Qwen, etc.). Experience with FastAPI, Flask, or Django. Strong understanding of REST APIs and cloud platforms (AWS, Azure, or GCP). Knowledge of Docker, Kubernetes, and CI/CD pipelines. Familiarity with Git and software development best practices. Understanding of AI evaluation metrics, prompt optimization, and model monitoring.