Join Iris Software, a rapidly growing IT services company recognized among India's Top 25 Best Workplaces in the IT industry. We are a trusted technology partner for enterprises, empowering them through technology-enabled transformations across financial services, healthcare, transportation & logistics, and professional services.

At Iris, we focus on complex, mission-critical applications leveraging cutting-edge technologies like Application & Product Engineering, Data & Analytics, Cloud, DevOps, Data & MLOps, Quality Engineering, and Business Automation. Our culture, "Build Your Future. Own Your Journey.", emphasizes employee ownership, growth opportunities, and a platform where your voice and work create real impact. We offer personalized career development, continuous learning, and mentorship to help you achieve your best, both personally and professionally.

Design and develop advanced Generative AI solutions utilizing platforms such as Amazon Bedrock, Azure OpenAI Service, and Azure AI Foundry. Define robust AI solution architectures and implementation strategies aligned with business and technical goals. Architect and implement Retrieval-Augmented Generation (RAG), Graph RAG, and Agentic AI systems for diverse enterprise use cases.

Lead the development of intelligent AI agents, tool-calling workflows, and autonomous task execution frameworks. Design and implement multi-agent orchestration solutions using frameworks like LangGraph, and explore emerging frameworks such as AutoGen or CrewAI. Optimize prompt strategies, retrieval mechanisms, context orchestration, and response generation frameworks.

Develop prompt engineering pipelines, integrate vector databases, and create semantic search solutions. Design and implement scalable AI application development workflows using LangChain or LangGraph. Build scalable AI engineering architectures that include authentication, authorization, asynchronous processing, scheduling, multithreading, API governance, and enterprise deployment best practices.

Lead fine-tuning and model customization initiatives to enhance domain-specific AI performance. Define AI integration patterns and deployment approaches for complex enterprise application ecosystems. Design cloud-native AI integration patterns that support enterprise APIs, databases, messaging platforms, and event-driven architectures.

Establish comprehensive 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 issues 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.

This senior engineering role requires 6-8 years of experience in Generative AI and Agentic Framework Concepts, Cloud Application Integration & Deployment, FastAPI Framework, Python, AI Search Index, AI Agents & Tool Calling, Retrieval-Augmented Generation (RAG), Agentic AI Systems, LangGraph, LangChain, Vector Databases, and Prompt Engineering.

Key behavioral competencies include strong ownership in driving AI engineering excellence, effective collaboration with diverse teams and business stakeholders, and promoting innovation and quality through experimentation and continuous improvement. Applicants should possess strong analytical thinking for evaluating complex AI challenges, adaptability in managing evolving AI technologies and business requirements, and effective communication skills regarding AI solution design, risks, and opportunities.

High attention to detail across AI architecture, prompt design, workflow implementation, testing, and deployment is essential. Encouraging continuous improvement in AI engineering practices and promoting secure, scalable, and responsible AI engineering practices while balancing innovation, governance, and business objectives are also critical. This role is based onsite in Noida, UP, India.