Lead AI Engineer (Agentic AI & LLM Solutions)

About the Role We are looking for a Lead AI Engineer to design, build, and deliver next-generation Agentic AI solutions for enterprise applications. You will lead the development of intelligent AI agents, Retrieval-Augmented Generation (RAG) systems, and LLM-powered applications that solve real business challenges. The ideal candidate has strong hands-on experience with Large Language Models (LLMs) , AI orchestration frameworks, prompt engineering, data pipelines, and modern software engineering practices. You will collaborate with cross-functional teams to architect scalable AI solutions and mentor engineers in adopting AI best practices. Key Responsibilities Design, develop, and deploy enterprise-grade Agentic AI solutions using internal or commercial AI platforms. Build customer-facing AI applications powered by Large Language Models (LLMs) such as Claude, GPT, or similar models. Design, implement, and optimize Retrieval-Augmented Generation (RAG) pipelines. Develop intelligent AI workflows using prompt engineering, Model Context Protocol (MCP), tool calling, and agent orchestration. Build and maintain data ingestion and processing pipelines to support AI applications. Evaluate AI model performance and continuously improve response quality, accuracy, latency, and cost efficiency. Integrate AI capabilities with enterprise applications and backend services. Collaborate with Product, Engineering, Data, and Business teams to deliver AI-driven solutions. Lead technical design discussions, perform code reviews, and mentor junior engineers. Stay current with emerging AI technologies, frameworks, and industry best practices. Required Skills & Qualifications Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field. 5+ years of professional software engineering experience. Hands-on experience building applications using Large Language Models (LLMs) such as Claude, OpenAI GPT, Gemini, or similar. Strong experience designing and implementing RAG architectures. Experience with AI agents, prompt engineering, tool calling, and agent orchestration frameworks. Good understanding of Model Context Protocol (MCP) and modern AI workflows. Experience building and maintaining data pipelines for AI applications. Strong programming skills in Python . Experience developing REST APIs and integrating AI services into enterprise applications. Familiarity with vector databases and embedding models. Experience with Git, CI/CD pipelines, and Agile development methodologies. Excellent analytical, problem-solving, and communication skills. Nice to Have Experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks. Experience with vector databases such as Pinecone, Weaviate, Milvus, or Chroma. Knowledge of cloud platforms such as AWS, Azure, or Google Cloud. Experience with Docker and Kubernetes. Familiarity with MLOps practices and model deployment. Experience implementing AI governance, evaluation frameworks, and observability. Exposure to enterprise integrations and API development. Experience leading technical teams or mentoring engineers. EA Number: 11C4879