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 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.

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 Qualified
- 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

📌 Java Architect (Pune)
🏢 Infosys
📍 Pune