Senior Agentic AI Engineer – Python (6+ Years Experience | Remote | Immediate Joiners)

About the RoleOur client is seeking a Senior Agentic AI Engineer with strong Python expertise to build and deploy production-grade Agentic AI and Generative AI solutions.The ideal candidate should have strong hands-on experience with Python, AI Agents, RAG, LLMs, LangGraph/LangChain, APIs, and vector databases, with the ability to design scalable and reliable AI applications.Key ResponsibilitiesBuild and deploy Agentic AI and Generative AI applicationsDevelop scalable Python APIs, backend services, and microservicesBuild AI agents with tool calling, function calling, planning, reasoning, memory, and multi-step workflowsDesign and implement RAG pipelines and retrieval workflowsDevelop stateful workflows using LangGraph / LangChainIntegrate agents with APIs, databases, vector stores, enterprise systems, and external toolsWork with OpenAI, Azure OpenAI, Claude, Gemini, AWS Bedrock, and open-source LLMsDeploy and optimize AI applications on AWS, Azure, or GCPImplement evaluation, monitoring, observability, guardrails, and production best practicesOptimize applications for performance, latency, reliability, scalability, and costRequired Skills6+ years of strong Python experience, including backend development, REST APIs, microservices, FastAPI, and/or FlaskStrong production experience with Agentic AI, AI Agents, tool calling, planning, reasoning, orchestration, memory/state management, and human-in-the-loop workflowsStrong experience with RAG, including ingestion, chunking, embeddings, semantic/vector search, hybrid retrieval, reranking, and hallucination reductionExperience with OpenAI/GPT, Azure OpenAI, Claude, Gemini, AWS Bedrock, or open-source LLMsHands-on experience with LangGraph and/or LangChainExperience with vector databases such as Pinecone, FAISS, ChromaDB, Weaviate, Qdrant, Milvus, pgvector, Azure AI Search, or OpenSearchStrong understanding of Prompt Engineering, Context Engineering, structured outputs, function calling, and guardrailsStrong knowledge of REST APIs, SQL/NoSQL, Git, Docker, CI/CD, monitoring, logging, and API securityExperience with AWS, Azure, or GCPExperience with LLMOps/MLOps and production AI deploymentsNice to HaveMulti-agent systemsAgentic RAG / Advanced RAGGraph RAG / Knowledge GraphsAutoGen, CrewAI, or LlamaIndexMCP (Model Context Protocol)Kubernetes / ServerlessLLM evaluation and observabilityAI guardrails and prompt-injection mitigationFine-tuning / LoRA / PEFTKeywordsPython, Agentic AI, Generative AI, RAG, LLMs, LangGraph, LangChain, FastAPI, Flask, AI Agents, Tool Calling, Function Calling, Vector Databases, Pinecone, FAISS, ChromaDB, Qdrant, pgvector, OpenAI, Azure OpenAI, Claude, Gemini, AWS Bedrock, AWS, Azure, GCP, REST APIs, Microservices, Docker, CI/CD, LLMOps, MLOpsHashtags#Python #AgenticAI #GenerativeAI #RAG #LLM #LangGraph #LangChain #FastAPI #AIAgents #VectorDatabase #OpenAI #AzureOpenAI #AWSBedrock #AWS #Azure #GCP #LLMOps #MLOps #AIEngineering #Hiring #YMindsAI