Job Description:Key Responsibilities :- Design and develop AI agents and multi-agent systems for enterprise use cases.- Build agentic workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI or similar technologies.- Develop LLM-powered applications using OpenAI, Azure OpenAI, Gemini, Claude or equivalent models.- Implement RAG pipelines using vector databases and enterprise knowledge sources.- Integrate AI agents with APIs, databases, enterprise applications, search engines, and external tools.- Develop agent capabilities including planning, reasoning, memory, tool calling, task decomposition, and decision-making.- Build prompt engineering strategies and optimize LLM responses for accuracy and reliability.- Work with Python to develop scalable AI services and backend applications.- Implement evaluation, monitoring, guardrails, observability, and responsible AI practices.- Fine-tune or customize models where required and optimize inference performance.- Deploy AI solutions on AWS, Azure, or GCP using containers and CI/CD pipelines.- Collaborate with Data Scientists, ML Engineers, Software Engineers, Architects,



and business teams.- Troubleshoot and improve the performance, scalability, security, and reliability of AI applications.Required Skills :- Strong programming experience in Python.- Hands-on experience with Generative AI and Large Language Models (LLMs).- Strong understanding of Agentic AI concepts and autonomous AI workflows.- Experience with LangChain / LangGraph / AutoGen / CrewAI or similar frameworks.- Robust knowledge of RAG, embeddings, vector databases, semantic search, and knowledge retrieval.- Experience with prompt engineering and LLM orchestration.- Experience integrating REST APIs, tools, function calling, and enterprise systems.- Knowledge of FastAPI, Flask, or similar Python frameworks.- Experience with databases such as PostgreSQL, MongoDB, SQL Server or similar.- Experience with vector databases such as Pinecone, FAISS, Chroma, Weaviate, Milvus or equivalent.- Understanding of ML/AI lifecycle, model evaluation, monitoring, and deployment.- Good understanding of cloud platforms such as AWS, Azure, or GCP. (ref:hirist.tech)

📌 Agentic AI Engineer (Hyderabad)
🏢 Glauben Technologies
📍 Hyderabad