Role: Chief Architect - Artificial Intelligence (Google Cloud Portfolio) Location Options: Bay Area - California Job Description We are seeking a Chief AI Architect to define and drive the AI/GenAI architecture, solution strategy, and industrialization roadmap across a large-scale Google Cloud portfolio. This role is responsible for turning AI from experimentation into scalable, production-grade capabilities, enabling agentic workflows, platformized AI adoption, and measurable business outcomes across all engagements. Key Responsibilities 1. AI Architecture & Strategy Define the end-to-end AI architecture vision: GenAI, ML, Data platforms, Agent frameworks Establish reference architectures and reusable patterns for: Vertex AI, LLMs, multi-model orchestration Align AI strategy to: Business priorities Portfolio growth and differentiation 2. Agentic & GenAI Solution Design Lead design of: Agentic systems (multi-agent workflows, orchestration models) Enterprise GenAI applications Define patterns for: Prompt engineering Retrieval-Augmented Generation (RAG) Tool augmentation / API integration Ensure solutions are: Scalable Secure Production-ready 3. AI Industrialization & Platforms Drive AI platformization across the portfolio: Reusable components Shared services and APIs Build accelerators for: AI-led onboarding Validation Support workflows Establish AI as a horizontal capability across all towers (FDE, ISV, GWS, etc.) 4. Data & AI Integration Define architecture for: Data pipelines Feature stores Real-time and batch processing Ensure tight integration between: Data platforms (BigQuery, Dataflow, etc.) AI/ML models Enable data-to-AI lifecycle maturity 5. Governance, Risk & Responsible AI Establish AI governance frameworks: Model evaluation Bias and safety checks Explainability Ensure compliance with: Security, privacy, and regulatory standards Define guardrails for enterprise AI adoption 6. CXO Advisory & AI Evangelization Act as the AI thought leader for client CXOs Lead: AI strategy discussions Innovation workshops Executive demos Translate AI capabilities into: Business outcomes ROI-driven transformation cases 7. Deal Support & Technical Differentiation Anchor the AI narrative in all strategic deals Work with BRMs and CTO to: Shape AI-led solutions Position differentiated value propositions Support high-impact: RFP s Orals Executive pitches 8. Talent & Capability Building Define capability roadmap for: AI engineers Data scientists FDEs with AI specialization Drive: AI bootcamps Certification pathways Build a high-caliber AI engineering ecosystem Required Qualifications 1520+ years of experience in: AI/ML architecture, data platforms, or advanced engineering roles Deep expertise in: GenAI (LLMs, RAG, agent frameworks) Cloud AI ecosystems (preferably Google Cloud / Vertex AI) Strong track record in: Designing and deploying enterprise-grade AI systems Preferred Qualifications Experience in: Agentic systems / autonomous workflows AI platform engineering and MLOps Exposure to: Multi-cloud AI environments Strong executive communication and thought leadership presence Success Metrics (What Good Looks Like) AI embedded across all major workflows and solutions High adoption of AI accelerators and reusable components Measurable business impact (cycle time reduction, cost savings, productivity gains) Strong AI-led differentiation in deals and client engagements Mature AI governance and production-grade implementations Salary Range: $239,300 - $282,000 a year #LI-AD1