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

Our 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 Responsibilities

• Build and deploy Agentic AI and Generative AI applications
• Develop scalable Python APIs, backend services, and microservices
• Build AI agents with tool calling, function calling, planning, reasoning, memory, and multi-step workflows
• Design and implement RAG pipelines and retrieval workflows
• Develop stateful workflows using LangGraph / LangChain
• Integrate agents with APIs, databases, vector stores, enterprise systems, and external tools
• Work with OpenAI, Azure OpenAI, Claude, Gemini, AWS Bedrock, and open-source LLMs
• Deploy and optimize AI applications on AWS, Azure, or GCP
• Implement evaluation, monitoring, observability, guardrails, and production best practices
• Optimize applications for performance, latency, reliability, scalability, and cost

Required Skills

• 6+ years of strong Python experience, including backend development, REST APIs, microservices, FastAPI, and/or Flask
• Strong production experience with Agentic AI, AI Agents, tool calling, planning, reasoning, orchestration, memory/state management, and human-in-the-loop workflows
• Strong experience with RAG, including ingestion, chunking, embeddings, semantic/vector search, hybrid retrieval, reranking, and hallucination reduction
• Experience with OpenAI/GPT, Azure OpenAI, Claude, Gemini, AWS Bedrock, or open-source LLMs
• Hands-on experience with LangGraph and/or LangChain
• Experience with vector databases such as Pinecone, FAISS, ChromaDB, Weaviate, Qdrant, Milvus, pgvector, Azure AI Search, or OpenSearch
• Strong understanding of Prompt Engineering, Context Engineering, structured outputs, function calling, and guardrails
• Strong knowledge of REST APIs, SQL/NoSQL, Git, Docker, CI/CD, monitoring, logging, and API security
• Experience with AWS, Azure, or GCP
• Experience with LLMOps/MLOps and production AI deployments

Nice to Have

• Multi-agent systems
• Agentic RAG / Advanced RAG
• Graph RAG / Knowledge Graphs
• AutoGen, CrewAI, or LlamaIndex
• LLM evaluation and observability
• AI guardrails and prompt-injection mitigation

Keywords