Gen AI - Senior Engineer

Iris Software, Inc.; India; On-site; INR 900,000 - 1,800,000; Full time

Job summary

Iris Software in India is seeking a seasoned GenAI engineer to design and deploy enterprise AI solutions across platforms. You will craft scalable AI architectures, optimize prompts, and guide deployments with a strong focus on governance and reliability.

The role emphasizes LangChain, Retrieval-Augmented Generation, and agentic AI workflows, with opportunities to mentor peers and contribute to cutting-edge projects.

Qualifications

• Expertise in GenAI concepts and AI system design.
• Experience with cloud-based AI integration.
• Proficiency in Python and AI services.
• Knowledge of LangChain and agentic architectures.

Responsibilities

• Design and deploy enterprise GenAI solutions across platforms.
• Define AI architectures aligned with business goals.
• Develop RAG and agentic workflows for enterprise use cases.
• Lead multi-agent orchestration and prompt strategies.
• Mentor team on GenAI frameworks and best practices.

Skills

GenAI Concepts

Cloud App Integration

Python

Azure OpenAI

Agentic AI Systems

LangChain

Tools

LangGraph

Job description

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Why Join Iris?

Are you ready to do the best work of your career at one of India’s Top 25 Best Workplaces in IT industry? Do you want to grow in an award-winning culture that truly values your talent and ambitions? Join Iris Software — one of the fastest-growing IT services companies— where you own and shape your success story.

About Us

At Iris Software, our vision is to be our client’s most trusted technology partner, and the first choice for the industry’s top professionals to realize their full potential.

With over 4,300 associates across India, U.S.A, and Canada, we help our enterprise clients thrive with technology-enabled transformation across financial services, healthcare, transportation & logistics, and professional services.

Our work covers complex, mission-critical applications with the latest technologies, such as high-value complex Application & Product Engineering, Data & Analytics, Cloud, DevOps, Data & MLOps, Quality Engineering, and Business Automation.

Working with Us

At Iris, every role is more than a job — it’s a launchpad for growth.

Our Employee Value Proposition, “Build Your Future. Own Your Journey.” reflects our belief that people thrive when they have ownership of their career and the right opportunities to shape it.

We foster a culture where your potential is valued, your voice matters, and your work creates real impact. With cutting-edge projects, personalized career development, continuous learning and mentorship, we support you to grow and become your best — both personally and professionally.

Curious what it’s like to work at Iris? Head to this video for an inside look at the people, the passion, and the possibilities. Watch it here .

Job Description

Mandatory Skills

Advanced GenAI & Agentic Framework Concepts, Cloud Application Integration & Deployment, Python, Azure OpenAI Service, Agentic AI Systems, AI Agents & Tool Calling, LangChain

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.

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.
• Applies strong analytical thinking to evaluate complex AI, retrieval, and orchestration challenges.
• Demonstrates adaptability while managing evolving AI technologies, frameworks, and business requirements.
• Communicates effectively regarding AI solution design, risks, dependencies, assumptions, and improvement opportunities.
• Maintains high attention to detail across AI architecture, prompt design, workflow implementation, testing, and deployment activities.
• Encourages continuous improvement in AI engineering practices, framework adoption, and solution effectiveness.
• Promotes secure, scalable, and responsible AI engineering practices while balancing innovation, governance, and business objectives.
• Supports knowledge sharing and mentoring to strengthen team capabilities.
• Balances innovation, scalability, reliability, and business priorities while driving delivery excellence.

Data & AI - GEN AI - Workflow & Agentic Frameworks (LangChain / LangGraph)

Data & AI - GEN AI - Python

Data & AI - GEN AI - Retrieval Augmented Generation (RAG) / Graph RAG / Agentic AI Systems

Data & AI - GEN AI - NumPy

Data & AI - GEN AI - Prompt Engineering / Vector Databases

Perks and Benefits for Irisians

Iris provides world-class benefits for a personalized employee experience. These benefits are designed to support financial, health and well-being needs of Irisians for a holistic professional and personal growth. Click here to view the benefits.