Gen AI Fullstack - Senior Engineer

Iris Software, Inc.; Dadri; Vor Ort; INR 2.400.000 - 3.600.000; Vollzeit

Zusammenfassung

Iris Software, Noida is seeking a Gen AI Fullstack - Senior Engineer to design and implement enterprise Generative AI solutions across multiple platforms. The role emphasizes architecture, RAG and agentic systems, and scalable AI engineering practices.

You will lead model customization, integration patterns, and governance to ensure reliable, enterprise-grade AI delivery within a modern cloud-native framework.

Aufgaben

• Design enterprise Gen AI solutions using Bedrock, Azure OpenAI, Azure AI Foundry, Grog, or AI Search Index platforms.
• Define AI solution architectures aligned with business and technical objectives.
• Design 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 multi-agent orchestration using LangGraph; evaluate AutoGen or CrewAI as appropriate.
• Design and optimize prompt strategies, retrieval mechanisms, context orchestration, and response generation frameworks.
• Build prompt engineering pipelines, vector DB integration, semantic search, and Retrieval-Augmented Generation architectures.
• Create LangChain/LangGraph workflows to support scalable AI app development.
• Develop scalable AI architectures with authentication, async processing, scheduling, multithreading, API governance.
• Lead fine-tuning and model customization for domain-specific AI performance.
• Define AI integration patterns and deployment approaches for enterprise ecosystems.
• Design cloud-native AI integration patterns for APIs, databases, messaging, and events.
• Establish evaluation frameworks for AI response quality, reliability, and relevance.
• Design HITL workflows to improve AI quality, governance and reliability.
• Review AI solution designs for engineering standards and responsible AI practices.
• Mentor team members on GenAI frameworks, RAG architectures, and AI engineering best practices.
• Drive continuous improvements in AI solution quality, innovation and operations.

Jobbeschreibung

Gen AI Fullstack - Senior Engineer

Noida

Iris Software

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.

Behavioral Competencies

• Demonstrates strong ownership while driving AI engineering excellence.
• Collaborate effectively with various teams and business stakeholders to ensure smooth delivery.
• Promotes innovation and quality-focused engineering through proactive experimentation and continuous improvement.