Technical Architect

Iris Software Inc.; Dadri; On-site; INR 5,000,000 - 11,000,000; Full time

Job summary

Iris Software Inc. in India seeks a visionary Generative AI Architect to lead enterprise-scale AI design and deployment. You will shape AI strategy, architect large-scale GenAI solutions, and drive production-grade platforms across cloud environments.

The role requires deep expertise in LLMs, RAG, multi-agent systems, and MLOps, with strong leadership to partner with stakeholders and guide POCs to production success.

Qualifications

• Experience designing enterprise-scale GenAI architectures.
• Proven ability to lead architecture governance and design reviews.
• Experience with AI safety, responsible AI standards, and prompt engineering.
• Strong collaboration with business stakeholders.

Responsibilities

• Define enterprise-wide GenAI strategy and architecture roadmap.
• Design end-to-end GenAI solutions aligned with business objectives.
• Architect scalable, secure, and production-ready AI platforms.
• Drive architecture governance, design reviews, and technical best practices.
• Lead POCs, pilots, and enterprise implementations.

Skills

GenAI architecture

LLMs

Agentic AI

RAG architectures

Cloud-native platforms

Kubernetes

Docker

MLOps

Stakeholder leadership

Security & scalability

Tools

Kubernetes

Docker

AWS

Azure

GCP

Vector databases

Job description

We are looking for a highly accomplished Generative AI Architect to lead the design, development, and deployment of enterprise-scale AI solutions. The ideal candidate will drive AI transformation initiatives by architecting solutions leveraging Large Language Models (LLMs), Agentic AI, RAG (Retrieval-Augmented Generation), Multi-Agent Systems, AI Orchestration Frameworks, and Cloud-Native Platforms.

This role requires a blend of AI architecture, software engineering, cloud architecture, enterprise integration, and stakeholder leadership to deliver innovative and scalable Gen AI products.

Key Responsibilities

• Define enterprise-wide Generative AI strategy and architecture roadmap.
• Design end-to-end GenAI solutions aligned with business objectives.
• Architect scalable, secure, and production-ready AI platforms.
• Drive architecture governance, design reviews, and technical best practices.

Generative AI & Agentic AI

• Design and implement solutions using GPT, Claude, Gemini, Llama, or equivalent LLMs.
• Architect Agentic AI systems with planning, reasoning, memory, orchestration, and tool execution capabilities.
• Develop AI agents capable of interacting with enterprise applications through APIs and tools.
• Define prompt engineering, evaluation, guardrails, and responsible AI standards.

RAG & Knowledge Systems

• Design Retrieval-Augmented Generation (RAG) architectures.
• Build document ingestion, chunking, embedding, indexing, and retrieval pipelines.
• Implement vector databases and semantic search capabilities.
• Optimize relevance, grounding, and hallucination reduction techniques.
• Integrate AI solutions with enterprise applications, databases, APIs, and business workflows.
• Design MCP (Model Context Protocol) and function-calling frameworks for AI-driven automation.
• Enable conversational AI, intelligent assistants, and business process automation.
• Architect AI workloads on AWS, Azure, or GCP.
• Design containerized deployments using Kubernetes and Docker.
• Implement CI/CD, MLOps, LLMOps, monitoring, and governance frameworks.
• Ensure scalability, resiliency, observability, and security of AI platforms.

Leadership & Stakeholder Management

• Partner with business leaders to identify and prioritize AI use cases.
• Lead architecture discussions with clients and executive stakeholders.
• Mentor engineering teams and drive AI capability development.
• Provide technical leadership for POCs, pilots, and enterprise implementations.