Responsibilities :
Key Responsibilities 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.
Additional Responsibilities:
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
Technical and Professional Requirements:
Must Have Skills 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
