Gen AI Engineer

Generative AI Engineer (Multi-Agent AI & RAG)

📍 Location: Hyderabad / Bangalore / Noida / Gurgaon

🏠 Work Model: Hybrid / Remote

📅 Working Days: 5 Days a Week

💼 Experience: 6+ Years

Role Overview

We are seeking an experienced Generative AI Engineer with strong expertise in Multi-Agent AI Systems and RAG (Retrieval-Augmented Generation) Architecture. The ideal candidate should have hands-on experience designing, developing, and deploying enterprise-grade AI solutions powered by LLMs, agent orchestration, semantic retrieval, and intelligent automation.

Key Responsibilities

• Design and develop enterprise-scale Multi-Agent AI solutions.
• Build and optimize RAG architectures, including ingestion, chunking, embeddings, vector indexing, retrieval, and grounded response generation.
• Develop agent workflows involving orchestration, tool calling, routing, memory, and decision-making.
• Integrate AI applications with enterprise systems, APIs, databases, and knowledge repositories.
• Implement prompt engineering, evaluation mechanisms, guardrails, and hallucination-reduction strategies.
• Build scalable backend services and APIs for AI-powered applications.
• Deploy, monitor, and optimize AI solutions in cloud environments.

Mandatory Requirements

• 4+ years of overall IT experience.
• Strong experience in Generative AI and LLM-based applications.
• Hands-on Multi-Agent Development experience (Mandatory).
• Hands-on RAG Architecture experience (Mandatory).
• Experience with vector databases, embeddings, semantic search, and retrieval systems.
• Strong proficiency in Python and API development.
• Experience building and deploying production-grade AI solutions.

Preferred Qualifications

• BE/BTech, ME/MTech, or MS from a reputed institution.
• Experience with enterprise AI, agentic workflows, and large-scale knowledge systems.
• Exposure to cloud platforms, containerization, CI/CD, and AI observability.

Ideal Candidate

• Has built real-world Multi-Agent systems, not just supporting tools or integrations.
• Has deep expertise in RAG implementation and optimization.
• Can independently architect, develop, and deploy enterprise GenAI solutions.