AI Architect- Agentic AI & RAG
DatamaticsMaharashtra, India1 day ago
Job description5 years of hands-on experience in Python with exposure to building AI / NLP applications. Practical experience with LLM tools like LangChain, LlamaIndex , or equivalent. Experience building RAG systems using vector stores and document loaders. Familiarity with LLM APIs such as OpenAI, Cohere, or HuggingFace models. Understanding of prompt design , embedding models (e.g., OpenAI, BGE, SentenceTransformers). Working knowledge of REST APIs , JSON , and integrating AI agents with backend systems.
Job Overview :
We are looking for an experienced AI Architect to lead solution design and development efforts in the areas of Agentic AI and Retrieval-Augmented Generation (RAG) . The ideal candidate will have strong experience working with large language models (LLMs), building intelligent applications using frameworks like LangChain or LlamaIndex, and designing scalable AI pipelines.
Key Responsibilities :
- Design and implement RAG-based systems combining LLMs with vector databases and internal document sources.
- Build task-based AI agents (e.g., chatbots, assistants) that can perform multi-step operations and integrate with external tools or APIs.
- Develop and maintain prompt templates , embedding pipelines, and orchestrators using frameworks like LangChain, LlamaIndex , etc.
- Work with data and ML teams to connect AI applications with enterprise knowledge sources (SharePoint, Confluence, databases, etc.).
- Evaluate and integrate embedding models , vector databases (FAISS, Pinecone, Chroma), and LLM APIs (OpenAI, Azure OpenAI, etc.).
- Collaborate with cross-functional teams to identify use cases, define architecture, and deliver PoCs or MVPs.
- Contribute to CoE documentation, reusable components, and architecture patterns for RAG and agent-based solutions.
Required Skills :
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Agentic Ai Architect • Maharashtra, India