NOIDA · FULLTIME
Lead Data Scientist
Iris Software
Noida · onsite · Posted 1d ago
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Undisclosed9–11 yrsfulltimeNoida
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Section · 01
About this role
Job Title
Lead Data Scientist
Location: Noida
Company: Iris Software
Job Description Mandatory Skills - Advanced GenAI Agentic Framework Concepts
- Cloud Application Integration Deployment
- Agentic AI Systems
- Retrieval-Augmented Generation (RAG)
- Azure OpenAI Service
- AI Agents Tool Calling
- LangChain
- Define and drive enterprise Generative AI strategy aligned with organizational objectives, innovation goals, and AI transformation initiatives.
- Establish AI engineering standards, governance frameworks, and best practices for enterprise AI solution delivery.
- Lead the design of enterprise-scale AI architecture using Amazon Bedrock, Azure OpenAI Service, Azure AI Foundry, Grog, or AI Search Index platforms.
- Define enterprise standards for Retrieval-Augmented Generation (RAG), Graph RAG, Agentic AI systems, and intelligent automation architectures. Drive adoption of AI agents, tool-calling frameworks, and autonomous workflow solutions across business functions.
- Drive adoption of enterprise multi-agent architectures, Human-in-the-Loop (HITL) governance, and scalable AI engineering patterns supporting secure and reliable business automation.
- Establish governance standards for model customization, fine-tuning, prompt engineering, retrieval quality, and AI solution lifecycle management.
- Define enterprise standards for prompt engineering pipelines, vector databases, semantic search, Retrieval-Augmented Generation, Model Context Protocol (MCP), and AI agent orchestration frameworks.
- Define architecture patterns and engineering standards using LangChain, LangGraph, and related workflow orchestration frameworks.
- Establish enterprise AI engineering standards covering secure API design, authentication, authorization, asynchronous processing, scheduling, scalability, deployment, observability, and operational resilience.
- Establish cloud integration and deployment standards for scalable and secure AI-enabled applications.
- Establish enterprise integration standards supporting databases, enterprise APIs, messaging platforms, and cloud-native AI application deployment.
- Lead architecture reviews and ensure AI solutions meet scalability, reliability, maintainability, explainability, and business value objectives.
- Guide teams on GenAI architecture, agentic systems, AI governance, and enterprise AI adoption best practices.
- Identify AI-related risks, governance gaps, operational challenges, and architectural limitations while defining mitigation strategies.
- Collaborate with various teams and leadership stakeholders to align AI initiatives with organizational objectives.
- Drive continuous improvement initiatives focused on AI maturity, innovation, operational effectiveness, governance, and business value realization.
- Data AI - GEN AI - Prompt Engineering / Vector Databases
- Data AI - GEN AI - Workflow Agentic Frameworks (LangChain / LangGraph)
- Data AI - GEN AI - Fine tuning Model Customization / AI Agents Tool Calling
- Data AI - GEN AI - Retrieval Augmented Generation (RAG) / Graph RAG / Agentic AI Systems
- Data AI - GEN AI - Azure OpenAI Service
- Data AI - GEN AI - Pandas
- Data AI - GEN AI - NumPy
- Data AI - GEN AI - Cloud Application Integration Deployment
- Data AI - GEN AI - Advanced GenAI Agentic Framework Concepts
- Data AI - GEN AI - Python
- Beh - Communication and collaboration
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Section · 02
Skills
AutomationBedrockApplication DeploymentAzure Aiapisapi designAzure OpenAIai governanceAnalyticsCloud Application Integrationbusiness automationAsynchronouscloudArchitectureAi SolutionsMicrosoft AzureCloud IntegrationArtificial Intelligence
Section · Company
About Iris Software
Iris Software
IT Services & Consulting
4.3k+
employees
1991
35 years old
Edison, New Jersey
United States (USA)
About
IT company for best tech-solutions to enhance business operations
Industries
IT Services & Consulting
Employee ratings
1,895 reviews
3.8/ 5
Culture
3.7
Career growth
3.3
Work-life
3.8
Employees rate it well for
Work Life Balance381Work Culture267Senior Management254Learning202Salary156
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