GenAI Architect

Iris Software, Inc.; Dadri; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Iris Software, Inc. seeks a GenAI Solutions Architect to lead enterprise-grade GenAI and Agentic AI initiatives, translating business needs into scalable, secure AI platforms. You will own the technical vision from discovery to production deployment and optimization.

The role requires designing end-to-end GenAI architectures, evaluating models and platforms, and establishing LLMOps with guardrails and Responsible AI practices, while guiding workshops and demonstrations.

Qualifications

• 12-15 years in software engineering, AI/ML, cloud or solution architecture.
• 3+ years hands-on Generative AI / LLM-based solutions.
• Proven experience operating as a Solution Architect, Technical Architect, GenAI Lead or equivalent.
• Bachelor's or Master's degree in Computer Science, Engineering, AI or a related discipline.

Responsibilities

• Lead the architecture and delivery of enterprise-grade Generative AI and Agentic AI solutions, translating business requirements into scalable, secure, and production-ready AI platforms.
• Own the technical vision from discovery and PoC through production deployment and optimization.
• Design end-to-end GenAI, RAG, Agentic AI and multi-agent architectures.
• Define solution patterns covering LLMs, embeddings, vector databases, orchestration, APIs, data pipelines and enterprise integrations.
• Architect AI agents with tool/function calling, workflow orchestration, memory, Human-in-the-Loop and MCP-based integrations.
• Evaluate and select appropriate foundation models, AI platforms and architecture patterns based on quality, latency, security and cost.
• Design solutions using Azure OpenAI / Azure AI Foundry, Amazon Bedrock / AgentCore, Google Vertex AI or equivalent platforms.
• Establish LLMOps, evaluation, observability, guardrails and Responsible AI practices.
• Define scalable cloud-native deployment architectures using APIs, containers, Kubernetes, serverless and asynchronous/event-driven patterns.
• Ensure architecture meets enterprise requirements for security, privacy, resilience, scalability, compliance and cost optimization.
• Lead architecture workshops, technical design reviews, PoCs and solution demonstrations.
• Create reference architectures, technical standards and reusable accelerators for GenAI adoption.
• Partner with business, product, security, data and engineering stakeholders to drive solutions from use case identification to production adoption.

Skills

Generative AI

LLMs

Agentic AI

AI solution architecture

RAG & embeddings

Vector search

LangGraph

LangChain

Cloud platforms (Azure/AWS/GCP)

Python

REST APIs

Microservices

LLMOps/MLOps

Education

Bachelor's or Master's in Computer Science/Engineering/AI

Tools

LangGraph

LangChain

Microsoft Agent Framework

Semantic Kernel

Bedrock Agents/AgentCore

Docker

Kubernetes

CI/CD

Infrastructure as Code

Observability platforms

Job description

GenAI Solutions Architect

Role Purpose

• Lead the architecture and delivery of enterprise-grade Generative AI and Agentic AI solutions, translating business requirements into scalable, secure, and production-ready AI platforms.
• Own the technical vision from discovery and PoC through production deployment and optimization.

Key Responsibilities

• Design end-to-end GenAI, RAG, Agentic AI and multi-agent architectures.
• Define solution patterns covering LLMs, embeddings, vector databases, orchestration, APIs, data pipelines and enterprise integrations.
• Architect AI agents with tool/function calling, workflow orchestration, memory, Human-in-the-Loop and MCP-based integrations.
• Evaluate and select appropriate foundation models, AI platforms and architecture patterns based on quality, latency, security and cost.
• Design solutions using Azure OpenAI / Azure AI Foundry, Amazon Bedrock / AgentCore, Google Vertex AI or equivalent platforms.
• Establish LLMOps, evaluation, observability, guardrails and Responsible AI practices.
• Define scalable cloud-native deployment architectures using APIs, containers, Kubernetes, serverless and asynchronous/event-driven patterns.
• Ensure architecture meets enterprise requirements for security, privacy, resilience, scalability, compliance and cost optimization.
• Lead architecture workshops, technical design reviews, PoCs and solution demonstrations.
• Create reference architectures, technical standards and reusable accelerators for GenAI adoption.
• Partner with business, product, security, data and engineering stakeholders to drive solutions from use case identification to production adoption.

Required Skills

• Strong expertise in Generative AI, LLMs, Agentic AI and AI solution architecture.
• Hands-on experience with RAG, embeddings, vector search and semantic retrieval.
• Experience with agent frameworks such as LangGraph, LangChain, Microsoft Agent Framework, Semantic Kernel, Bedrock Agents/AgentCore or equivalent.
• Strong understanding of multi-agent orchestration, tool calling, context engineering, memory and Human-in-the-Loop patterns.
• Experience with one or more cloud AI ecosystems: Azure, AWS or GCP.
• Strong knowledge of Python, REST APIs, microservices and distributed/cloud-native architectures.
• Experience with LLM evaluation, tracing, monitoring, prompt/model versioning and LLMOps/MLOps.
• Understanding of AI security, guardrails, Responsible AI, identity/access management and data governance.
• Ability to assess architectural trade-offs across accuracy, latency, scalability, reliability and cost.

Preferred Experience

• Experience delivering multiple enterprise GenAI solutions from PoC to production.
• Exposure to multimodal AI, knowledge graphs, fine-tuning/model customization and advanced retrieval techniques.
• Experience with Docker, Kubernetes, CI/CD, Infrastructure as Code and observability platforms.
• Cloud or architecture certifications across Azure, AWS, GCP or TOGAF are advantageous.

Experience & Qualifications

• 12-15 years of overall experience in software engineering, AI/ML, cloud or solution architecture.
• 3+ years of hands-on experience with Generative AI / LLM-based solutions preferred.
• Proven experience operating as a Solution Architect, Technical Architect, GenAI Lead or equivalent.
• Bachelors or Masters degree in Computer Science, Engineering, AI or a related discipline.

Compensation

Best in the industry, commensurate to experience and skills of the aspirant.