using frameworks such as LangChain, LangGraph, LangFlow, CrewAI, Autogen etc. Engineer and tune prompts to enhance performance and reliability of generative tasks. Design RAG systems using vector databases (Pinecone, FAISS, Chroma, PosgreSQL etc.) for contextual retrieval. Incorporate semantic search and embedding strategies for more relevant and grounded LLM responses. Familiar with Guardrails to implement applications which follow responsible AI guidelines. More ❯
LangChain and LLMs (eg, OpenAI, Claude, Mistral, etc.) Develop Python-based services and APIs for integration with AI models Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases (eg, FAISS, Weaviate) Collaborate with data scientists and DevOps to deploy AI models into production Contribute to prompt engineering and fine-tuning strategies for LLMs Ensure solutions meet governance, ethical, and security … Skills: Proven experience as an AI Engineer or Machine Learning Engineer Strong Python development skills Hands-on experience with LangChain and other LLM frameworks Familiarity with vector databases (eg, FAISS, Pinecone, Weaviate) Experience working with OpenAI, Anthropic, or other generative AI APIs Ability to work independently in a remote team and deliver results to tight timelines Desirable Skills: Knowledge of More ❯
refining prompts for LLMs (OpenAI, Claude, etc.) Building prompt libraries and evaluation frameworks Structuring unstructured data (PDFs, notes, forms) into usable formats Working with RAG pipelines and vector databases (FAISS, Pinecone, etc.) Embedding LLMs into user-facing healthcare tools (e.g., AI assistants, in-context help) Collaborating with product, design, and clinical teams to ship real features What You’ll Bring More ❯
refining prompts for LLMs (OpenAI, Claude, etc.) Building prompt libraries and evaluation frameworks Structuring unstructured data (PDFs, notes, forms) into usable formats Working with RAG pipelines and vector databases (FAISS, Pinecone, etc.) Embedding LLMs into user-facing healthcare tools (eg, AI assistants, in-context help) Collaborating with product, design, and clinical teams to ship real features What You'll Bring More ❯
