Description

You will architect, build, and deploy production-grade RAG systems and autonomous AI agents, owning the end-to-end lifecycle from retrieval loops to generation and evaluation.

This role is on-site.

Responsibilities

• Architect AI agents and multi-agent workflows using LangGraph and related frameworks.
• Build and deploy RAG systems for knowledge-intensive applications, including retrieval, generation, and evaluation loops.
• Evaluate, integrate, and optimize LLMs for quality, latency, cost, and reliability in production.
• Establish coding standards, security practices, and MLOps processes for AI systems.
• Lead delivery planning, risk management, and mentoring through code reviews and technical guidance.

Required Skills

• 10+ years of relevant experience building and deploying AI/LLM systems.
• Practical Gen AI development experience with Python.
• Agentic AI concepts and implementation experience for autonomous workflows.
• RAG system development and LLM evaluation/integration in production.
• Strong background in Artificial Intelligence and AI engineering.
• Experience with LLM development and optimization.
• Proficiency in LangChain and LangGraph for orchestration.
• Advanced degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

Key Skills

Education

Any Graduate