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