Job Summary

Fullstack Gen AI - Senior Engineer

Location

Noida, UP, India

Company

Iris Software

Job Description 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.




- Define AI integration patterns and deployment approaches for enterprise application ecosystems.
- Design cloud-native AI integration patterns supporting enterprise APIs, databases, messaging platforms, and event-driven architectures.
- Establish evaluation frameworks for AI response quality, reliability, relevance, and consistency.
- Design Human-in-the-Loop (HITL) workflows and evaluation mechanisms to improve AI quality, governance, and business reliability.
- Review AI solution designs to ensure adherence to engineering standards, scalability, maintainability, and responsible AI practices.
- Troubleshoot complex AI workflow, retrieval, orchestration, and model behavior challenges through detailed root cause analysis.
- Mentor team members on GenAI frameworks, RAG architectures, agentic systems, and AI engineering best practices.
- Drive continuous improvement initiatives focused on AI solution quality, innovation, and operational effectiveness.

Mandatory Competencies
- DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - GitLab, Github, Bitbucket
- User Interface - UI-React - React
- Cloud - Azure - Azure Devops, Azure Pipelines, Azure CLI
- Data AI - GEN AI - Azure AI Foundry
- 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 - Python
- 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
- Beh - Communication and collaboration

📌 Fullstack Gen AI - Senior Engineer (Noida)
🏢 IRIS SOFTWARE
📍 Noida