Principal Technology Architect - AI and Enterprise Architecture

Infosys; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Infosys is seeking a Principal Technology Architect to lead AI/GenAI transformations across enterprise architecture and platform engineering. You will shape strategy, define target-state architectures, and drive governance, effectiveness, and value realisation on client programs.

The role emphasizes cloud platforms (Azure/AWS/GCP), Kubernetes, DevSecOps, and scalable AI-enabled software delivery, with strong client advisory responsibilities.

Qualifications

• Experience shaping AI transformation strategy and roadmaps.
• Proven ability to drive enterprise AI programs end-to-end.
• Strong governance, architecture design, and stakeholder management.
• Exposure to banking/payments domain is a plus.

Responsibilities

• Define enterprise AI transformation vision, roadmap, and target-state architecture.
• Identify AI use cases and transformation opportunities across business and technology domains.
• Develop AI adoption frameworks, governance models, and operating structures.
• Drive AI-first engineering practices across delivery organizations.
• Partner with CTOs and business leaders on transformation strategy and governance.

Skills

AI & GenAI

Generative AI

LLM architectures

Agentic AI

RAG architectures

AI governance

Enterprise Architecture

TOGAF

Cloud & Engineering

Kubernetes

DevSecOps

API & Microservices

Observability

SRE

Tools

Azure

AWS

GCP

Kubernetes

Job description

Principal Technology Architect

• AI & GenAI
• Generative AI and LLM architectures
• Agentic AI systems
• RAG architectures
• AI orchestration frameworks
• Prompt engineering and evaluation frameworks
• AI governance and Responsible AI
• Enterprise Architecture
• TOGAF or equivalent Enterprise Architecture framework
• Business and Technology Architecture
• Solution Architecture
• Architecture governance
• Technology strategy and roadmapping
• Cloud & Engineering
• Azure/ AWS / GCP
• Kubernetes and Container ecosystems
• DevSecOps and Platform Engineering
• API, Event-Driven, and Microservices Architecture
• Infrastructure as Code
• Reliability & Operations
• SRE
• Observability Platforms
• Resilience Engineering
• Performance Engineering
• Operational Excellence

Preferred Skills

• Banking & Payments domain expertise
• Digital Channels and Customer Platforms
• Core Banking modernization
• FinOps
• Quantum of Experience in AI-enabled SDLC transformation
• Product Operating Model experience

Certifications (Preferred)

• TOGAF
• Azure Solutions Architect Expert
• Azure AI Engineer Associate
• AWS Solutions Architect Professional
• Cloud Architect Certifications
• AI/ML Certifications
• SRE Foundation
• Kubernetes Certifications
• Anthropic Certifications

Success Metrics

The candidate will be measured on:

• AI transformation deals influenced and won
• AI use cases industrialized
• Reusable AI assets and accelerators created
• Client stakeholder satisfaction
• Architecture governance effectiveness
• Productivity gains through AI adoption
• Talent development and architect mentoring
• Revenue growth from transformation programs

AI Transformation Strategy

• Define enterprise AI transformation vision, roadmap, and target-state architecture.
• Identify AI use cases and transformation opportunities across business and technology domains.
• Develop AI adoption frameworks, governance models, and operating structures.
• Drive AI-first engineering practices across delivery organizations.

Enterprise Architecture

• Define business, application, data, technology, and security architecture blueprints.
• Develop modernization roadmaps for legacy platforms.
• Drive architecture governance and design assurance.
• Establish architecture standards, reference architectures, and reusable patterns.

AI & Data Platforms

• Architect enterprise AI platforms leveraging LLMs, Agentic AI, RAG, Knowledge Graphs, and AI orchestration frameworks.
• Define AI operating models, model lifecycle management, and responsible AI controls.
• Design AI-ready data architectures including Data Fabric, Lakehouse, and Knowledge Platforms.
• Drive integration of enterprise knowledge with AI ecosystems.

Engineering Transformation

• Drive adoption of AI-assisted software engineering.
• Establish platform engineering and developer productivity initiatives.
• Lead modernization using cloud-native and event-driven architectures.
• Promote reliability, observability, resilience, and security-by-design practices.

Client Advisory & Consulting

• Partner with CTOs and business executives on transformation strategy.
• Conduct maturity assessments and capability gap analyses.
• Develop business cases, value realization frameworks, and investment roadmaps.
• Lead executive workshops and transformation steering committees.

Innovation & Thought Leadership

• Create AI transformation assets, accelerators, frameworks, and industry solutions.
• Mentor architects and engineering leaders.
• Represent the organization in client forums and industry events.
• Publish reusable assets and best practices.