Java Architect

Java Architect

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 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 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.