Job Title: Lead Agentic AI Engineer

Experience: 5+ Years (40 LPA Max )
Location: Remote
Employment Type: Full-Time

Job Description

We are seeking a highly skilled Lead Agentic AI Engineer with 7+ years of software development experience, including strong expertise in Python, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. The ideal candidate will lead the design, architecture, and delivery of enterprise-scale AI solutions while mentoring engineering teams and driving technical innovation.

The role requires a hands-on technical leader with experience building production-grade AI agents, multi-agent systems, RAG pipelines, and scalable GenAI applications. The candidate should be capable of translating business requirements into robust AI solutions and collaborating with cross-functional teams to deliver high-impact AI products.

Key Responsibilities

• Lead the architecture, design, and development of enterprise-grade Agentic AI applications.
• Build and deliver end-to-end GenAI solutions using Python, LLMs, and RAG.
• Design and implement intelligent AI agents, multi-agent workflows, and tool integrations.
• Architect scalable RAG pipelines using vector databases and embedding models.
• Drive prompt engineering, retrieval optimization, and LLM performance tuning.
• Integrate AI solutions with enterprise applications, APIs, and cloud platforms.
• Establish best practices for AI application development, testing, deployment, and monitoring.
• Mentor and guide a team of AI engineers through code reviews and technical leadership.
• Collaborate with Product Managers, Data Scientists, and Solution Architects to define AI roadmaps and solution architecture.
• Evaluate emerging AI frameworks, LLMs, and Agentic AI technologies to drive innovation.

Required Skills

• 7+ years of hands-on experience in software development with Python.
• Strong expertise in Large Language Models (LLMs), Prompt Engineering, and RAG Architecture.
• Hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, or similar Agentic AI frameworks.
• Experience building multi-agent systems and AI orchestration workflows.
• Strong knowledge of vector databases such as Pinecone, FAISS, ChromaDB, Weaviate, or Milvus.
• Experience developing REST APIs using FastAPI or Flask.
• Good understanding of MCP (Model Context Protocol), tool/function calling, and AI workflow orchestration.
• Experience with Docker, Kubernetes, Git, CI/CD, and cloud platforms (AWS, Azure, or GCP).
• Knowledge of AI security, guardrails, observability, and production deployment best practices.