Live opening · Posted 23 hours ago

Gen AI Engineer

PeopleScout · Bengaluru, Karnataka, India (Hybrid)
Linkedin Hybrid
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At a glance

The key details from the original listing.

Posted 23 hours ago
CompanyPeopleScout
LocationBengaluru, Karnataka, India (Hybrid)
Work modeHybrid
SourceLinkedin
Listed23 hours ago

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About the role

Description supplied by the original job listing.

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.

Work arrangement
Hybrid

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