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Fullstack Gen AI - Senior Engineer
IRIS Software Inc
Noida, IND
Full-time
Senior
Onsite
Discovered 3 weeks ago
Amazon BedrockAzure OpenAI ServiceAzure AI FoundryAI Search IndexLangGraphAutoGen
Free
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Amazon BedrockAzure OpenAI ServiceAzure AI Foundry
Role Overview
Mandatory Skills: Advanced GenAI & Agentic Framework Concepts, Cloud Application Integration & Deployment, AI Agents & Tool Calling, Azure AI Foundry, Agentic AI Systems, LangChain, LangGraph Additional Skills: GitHub
Key Skills for This Role
Amazon BedrockAzure OpenAI ServiceAzure AI FoundryAI Search IndexLangGraphAutoGen
Full Job Posting
Mandatory Skills
- Advanced GenAI & Agentic Framework Concepts, Cloud Application Integration & Deployment, AI Agents & Tool Calling, Azure AI Foundry, Agentic AI Systems, LangChain, LangGraph Additional Skills: GitHub
Key Responsibilities
- Design and develop enterprise Generative AI solutions using Amazon Bedrock, Azure OpenAI Service, Azure AI Foundry, Grog, or AI Search Index platforms.
- Define AI solution architectures and implementation approaches aligned with business and technical objectives.
- Design and implement Retrieval-Augmented Generation (RAG), Graph RAG, and Agentic AI architectures for enterprise use cases.
- Lead development of intelligent AI agents, tool-calling workflows, and autonomous task execution frameworks.
- Design and implement multi-agent orchestration solutions using frameworks such as LangGraph and evaluate emerging frameworks such as AutoGen or CrewAI where appropriate.
- Design and optimize prompt strategies, retrieval mechanisms, context orchestration, and response generation frameworks.
- Design prompt engineering pipelines, vector database integration, semantic search solutions, and Retrieval-Augmented Generation architectures supporting enterprise AI applications.
- Design and implement workflows using LangChain or LangGraph to support scalable AI application development.
- Design scalable AI engineering architectures incorporating authentication, authorization, asynchronous processing, scheduling, multithreading, API governance, and enterprise deployment best practices.
- Lead fine-tuning and model customization initiatives to improve domain-specific AI performance.
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