Senior AI Engineer

3 hours ago

Gurugram, India questhiring Full time

Job Title : Senior AI Engineer Agentic AI SystemsRole Overview :We're seeking an experienced Senior AI Engineer to design and implement sophisticated agentic AI systems that can autonomously handle complex workflows. You'll be responsible for architecting AI agents that interact with various data sources, make intelligent decisions, and deliver actionable insights to our customers.This role represents a unique opportunity to pioneer enterprise-scale agentic AI implementation, establishing new paradigms for autonomous decision-making and intelligent automation.Key Responsibilities :- Design and deploy production-grade agentic AI systems that autonomously process customer documents and queries.- Architect retrieval-augmented generation (RAG) pipelines for large-scale document management and intelligent information extraction.- Implement multi-agent orchestration frameworks to coordinate specialized AI components.- Develop robust context management systems for handling extensive customer data efficiently and accurately.- Create and optimize AI workflow automation for dynamic customer requirements and business scenarios.- Ensure AI system reliability, scalability, and compliance with industry regulations.- Implement performance monitoring systems to track AI output quality, accuracy, and relevance.- Collaborate with cross-functional teams to integrate AI agents with existing business processes and systems.Required Qualifications :- 47 years of hands-on experience developing and deploying agentic AI systems in production environments.- Proven track record of building AI agents that autonomously handle complex tasks and decision-making using frameworks like LangGraph, LlamaIndex, ADK, etc.- Strong experience with RAG architectures, vector databases, and document processing pipelines.- Experience with production deployment of AI systems, including monitoring, testing, and optimization.- Proven experience designing quality metrics, feedback loops, and continuous improvement processes for AI systems.- Knowledge of enterprise-grade AI infrastructure and MLOps practices.- Understanding of AI safety, ethics, and compliance requirements. (ref:hirist.tech)

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