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We are seeking a seasoned AI Architect to join the Architecture & Technology Board, driving AI architecture direction and adoption across Service Delivery. This role ensures fit-for-purpose, scalable, and responsible AI usage aligned with enterprise goals, while enabling development teams to build consistent, reusable, and production-ready AI applications through strong governance and best practices.
Job Responsibility:
Architecture Governance & Standards
Define and govern AI/ML, GenAI, and data architecture standards, patterns, and guardrails
Review and approve AI-related solutions within the Architecture & Technology Forum
Ensure alignment with enterprise architecture, data governance, security, and compliance
Provide governance and guidance on AI platform capabilities including Model Context Protocol (MCP), Agent-to-Agent (A2A) communication, AI Gateways, and observability frameworks, ensuring secure, scalable, and well-orchestrated AI systems
Provide oversight on production-grade AI deployments, ensuring scalability, reliability, and observability
Ensure strong data lifecycle management including data quality, lineage, governance, and compliance
Establish and maintain baseline architecture for existing AI services and data ecosystems
Use Case Assessment & Fitment
Evaluate business use cases for AI applicability, feasibility, and value realization
Guide teams in selecting the right approach — AI vs. automation vs. traditional solutions
Ensure optimal technology fitment, avoiding overuse or misuse of AI
Enablement & Best Practices
Define and promote best practices for AI application design, data pipelines, and lifecycle management
Guide engineering teams on architecture patterns, integration approaches, and data flows
Enable reuse of AI components, datasets, and standardized solution patterns
Technology Leadership & Innovation
Stay current with the latest advancements in AI/ML, GenAI, and enterprise AI platforms
Evaluate emerging technologies and define adoption strategies for Service Delivery
Publish whitepapers, architectural guidelines, and thought leadership content on AI in Service Delivery
Collaboration & Reuse Across the Organization
Collaborate with architecture teams and innovation units to align on ongoing AI initiatives
Leverage and integrate existing platforms, solutions, and learnings to avoid duplication of efforts
Drive reuse, standardization, and alignment across units for consistent AI adoption
Act as a bridge between global initiatives and Service Delivery implementation
Requirements:
Strong experience in AI/ML architecture with hands-on exposure to AI application development
Proven experience governing or leading production-grade AI/ML deployments
Expertise in GenAI, LLMs, RAG architectures, and enterprise AI solution patterns
Solid understanding of data architecture fundamentals including data modelling, ETL/ELT pipelines, data quality, lineage, and governance
Experience with data platforms such as data lakes, warehouses, and streaming systems
Knowledge of feature stores, vector databases, and data foundations for AI/GenAI
Strong understanding of AI lifecycle management (MLOps) and data lifecycle management
Experience with cloud AI ecosystems (AWS, Azure, GCP) and integration patterns
Ability to assess business use cases and map them to appropriate AI or automation solutions
Experience defining architecture standards, guidelines, and governance frameworks
Strong communication and thought leadership capabilities including whitepapers, forums, and strategic presentations