NoidaOn-siteSenior
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On-site in Noida.
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Experience: 5-8 Years
Location: Noida
Mandatory Skills:
Agentic AI Systems, Advanced GenAI & Agentic Framework Concepts, Cloud Application Integration & Deployment, FastAPI Framework, Python, Graph RAG, Retrieval-Augmented Generation (RAG), AI Agents & Tool Calling, LangChain, LangGraph, Vector Databases, AI Search Index
Additional Skills:
PySpark
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.
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.
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