Gen AI Architect

Role: GenAI Architect
Experience: 8-14 Years
Location: Bangalore, Hyderabad, Pune, Chennai, Mumbai, Gurugram, or other Infosys locations
Employment Type: Full-Time

About Infosys

Infosys is a global leader in next-generation digital services and consulting. We enable clients to navigate their digital transformation journey by leveraging emerging technologies, including Artificial Intelligence, Generative AI, Cloud, Data, and Engineering. As part of our AI-first strategy, we are expanding our GenAI practice to create innovative solutions that drive business value at scale.

Role Overview

Infosys is seeking an experienced Generative AI Architect to lead the design, development, and implementation of enterprise-scale GenAI solutions. The ideal candidate will have deep expertise in Large Language Models (LLMs), AI architecture, cloud platforms, data engineering, and AI governance. This role involves collaborating with business stakeholders, data scientists, engineers, and client leadership teams to architect scalable and secure GenAI-powered applications.

The GenAI Architect will be responsible for establishing solution architecture, defining AI adoption strategies, designing reusable AI frameworks, and driving innovation using state-of-the-art AI technologies.

Key Responsibilities

Solution Architecture & Design

• Define end-to-end architecture for enterprise Generative AI solutions.
• Design scalable, secure, and production-ready AI platforms leveraging LLMs and foundation models.
• Architect Retrieval-Augmented Generation (RAG), AI Agents, Multi-Agent Systems, and Knowledge Management solutions.
• Create reusable AI solution patterns, accelerators, and reference architectures.
• Establish architecture standards, best practices, and governance frameworks for GenAI implementations.

AI/ML & GenAI Implementation

• Lead the design and deployment of LLM-powered applications using OpenAI, Azure OpenAI, Anthropic, Gemini, Llama, and other foundation models.
• Design prompt engineering frameworks and model optimization strategies.
• Implement vector databases, semantic search, embeddings, and knowledge retrieval solutions.
• Evaluate and recommend model selection, orchestration frameworks, and AI development tools.
• Drive adoption of emerging GenAI capabilities including Agentic AI and autonomous workflows.

Cloud & Platform Engineering

• Architect GenAI solutions on Azure, AWS, or Google Cloud platforms.
• Design scalable AI infrastructure including model serving, API gateways, security layers, and monitoring frameworks.
• Integrate GenAI solutions with enterprise systems, data platforms, and business applications.
• Define deployment strategies using containers, Kubernetes, and CI/CD pipelines.

Client Engagement & Leadership

• Work closely with clients to understand business requirements and translate them into technical solutions.
• Lead architecture discussions, technical workshops, and innovation sessions.
• Develop solution proposals, effort estimations, and implementation roadmaps.
• Provide thought leadership on GenAI trends, technologies, and best practices.
• Mentor data scientists, AI engineers, and development teams on GenAI architecture.

Governance & Responsible AI

• Define Responsible AI frameworks including fairness, explainability, privacy, and compliance.
• Establish guardrails for model security, hallucination mitigation, and content safety.
• Ensure compliance with enterprise security standards and regulatory requirements.
• Design monitoring and evaluation frameworks for AI model performance and reliability.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• 8-14 years of overall industry experience with at least 3+ years in AI/ML and Generative AI solution architecture.
• Strong experience designing enterprise-scale AI solutions.
• Proven experience leading architecture and consulting engagements.
• Excellent communication, stakeholder management, and leadership skills.

Technical Skills

Generative AI & LLMs

• Large Language Models (GPT, Llama, Claude, Gemini, Mistral)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Agentic AI and Multi-Agent Systems
• Fine-Tuning & Model Adaptation
• LLM Evaluation Frameworks
• Semantic Search & Embeddings

AI Frameworks & Tools

• LangChain
• LlamaIndex
• Semantic Kernel
• AutoGen
• CrewAI
• Hugging Face
• OpenAI APIs
• Azure AI Foundry

Programming & Data Technologies

• Python
• SQL
• PySpark
• REST APIs
• Data Engineering Concepts
• Vector Databases (Pinecone, Weaviate, ChromaDB, Azure AI Search)

Cloud Platforms

• Microsoft Azure
• AWS
• Google Cloud Platform

DevOps & MLOps

• Docker
• Kubernetes
• GitHub/GitLab
• Azure DevOps
• MLOps and LLMOps Frameworks
• Model Monitoring and Observability

Preferred Qualifications

• Experience with Microsoft Azure OpenAI and AI Foundry.
• Hands-on expertise in enterprise AI transformation programs.
• Experience implementing AI governance and Responsible AI frameworks.
• Working knowledge of data security, privacy, and compliance standards.
• Relevant certifications in Azure AI, AWS Machine Learning, Google AI, or Cloud Architecture.
• Experience in Banking, Retail, Healthcare, Manufacturing, Telecom, or Energy domains.

Key Competencies

• Enterprise Architecture Leadership
• Strategic Thinking and Innovation
• Client Relationship Management
• Solution Consulting
• Problem Solving and Decision Making
• Cross-functional Collaboration
• Presentation and Executive Communication Skills
• Team Mentoring and Technical Leadership