AI/ML Engineer (LLMs, AI Agents, RAG & Python) – Build Production-Ready AI Applications

We are looking for a skilled AI/ML Engineer to help build and deploy production-ready AI applications using modern LLMs and machine learning technologies. This is a hands-on engineering role for someone who has experience building real-world AI systems—not just prototypes. Responsibilities - Design and develop AI-powered applications using Python. - Build LLM-powered solutions with OpenAI, Claude, Gemini, or open-source models. - Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases such as Pinecone, Qdrant, Weaviate, or Chroma. - Build AI agents and multi-agent workflows using frameworks like LangChain, LangGraph, CrewAI, or AutoGen. - Create REST APIs with FastAPI or Flask. - Integrate AI solutions with third-party APIs and business workflows. - Deploy applications using Docker and cloud platforms (AWS, GCP, or Azure). - Optimize model performance, latency, and cost. Required Skills - Strong Python development experience. - Experience with LLMs, prompt engineering, and function calling. - Hands-on experience with LangChain, LangGraph, CrewAI, or similar frameworks. - Experience building RAG applications and semantic search systems. - Knowledge of vector databases (Pinecone, Qdrant, Weaviate, Chroma, or FAISS). - Experience with FastAPI, Docker, Git, and cloud deployment. - Understanding of embeddings, retrieval strategies, and AI system evaluation. Nice to Have - Experience with MCP (Model Context Protocol). - Experience with n8n, Make, or workflow automation. - Knowledge of speech, vision, or multimodal AI. - Experience with fine-tuning or open-source LLM deployment. What We're Looking For - Excellent problem-solving skills. - Strong communication and documentation. - Ability to write clean, maintainable, production-quality code. - Experience delivering AI products from idea to deployment. When Applying Please include: 1. A brief introduction. 2. Links to relevant GitHub repositories or portfolio. 3. Examples of AI/ML projects you've built. 4. Your experience with LLMs, RAG, and AI agents. 5. Your availability and estimated hourly rate. We're looking for someone who can become a long-term engineering partner if the collaboration goes well.