Enterprise Architect
Job Title: Google Cloud Platform Vertex Enterprise Architect Location: Fully Remote Employment Type: Contract To Hire
About the Role
We are looking for an Enterprise Architect to lead a global enterprise customer's AI roadmap and platform strategy on Google Cloud and Vertex AI. You will be the primary advisor for Google Cloud and Vertex AI adoption, defining scalable, secure, and governed AI architecture patterns and driving Agentic AI use cases across business functions. Why This Role Matters Drive enterprise-scale AI adoption aligned with business objectives Establish a unified AI platform strategy across business functions Accelerate value from Google Cloud and Vertex AI investments Ensure AI solutions are secure, governed, scalable, and production-ready Create reusable AI architecture patterns that reduce delivery timelines and risk
What You'll Do
Strategy & Advisory Define and evolve the Enterprise AI roadmap Provide executive-level recommendations on AI investments and platform choices Identify and prioritize high-value AI and Agentic AI use cases AI & Platform Architecture Design enterprise-scale Agentic AI and GenAI architectures Define reference architectures on Google Cloud and Vertex AI Establish standards for LLM usage, grounding, orchestration, and governance Architect multi-agent workflows and autonomous decision frameworks SAP & Enterprise Integration Design integrations with SAP S/4HANA using APIs, OData, and BAPIs Enable AI agents to securely interact with enterprise applications Define integration, data access, and workflow automation standards Security & Governance Define AI security architecture, IAM, RBAC, and access controls Establish auditability, compliance, human approvals, and AI guardrails Implement responsible AI governance and risk mitigation frameworks Delivery & Operations Define observability, monitoring, logging, and resiliency standards Drive production readiness reviews, SIT/UAT support, and deployment governance Mentor engineering teams and conduct architecture reviews
Required Qualifications
Education: Bachelor's or Master's in Computer Science, Engineering, IT, Data Science, AI, or a related field. Google Cloud, Vertex AI, AI/ML, Cloud Architecture, or Security certifications preferred. Experience: 12+ years overall IT experience 6+ years in Enterprise/Cloud Solution Architecture 4+ years in AI/ML, GenAI, or Enterprise AI initiatives 3+ years in Google Cloud Platform (Google Cloud Platform) and Vertex AI 2+ years designing and delivering Agentic AI / LLM-based solutions Must-Have Skills: Agentic AI / GenAI Solution Architecture: 4+ years Google Cloud Platform (Google Cloud Platform) & Vertex AI: 3+ years Enterprise AI/Cloud Architecture & Solution Design: 6+ years SAP S/4HANA Integration Architecture (OData/BAPI/API patterns): 3+ years Python & AI application architecture: 5+ years Agent orchestration, tool/API calling & workflow automation: 2+ years REST APIs / Enterprise Integration Architecture: 5+ years Security, IAM, service accounts, RBAC & enterprise governance: 4+ years Human-in-the-Loop, approval workflows, auditability & AI guardrails: 2+ years Production AI architecture: logging, monitoring, exception handling & resiliency: 3+ years Good to Have SAP Finance / month-end close process understanding: 2+ years Google Chat / notification and approval integration: 1+ year Web application / command-center architecture: 3+ years CI/CD and cloud deployment architecture: 3+ years SIT/UAT and enterprise production-readiness planning: 4+ years Agentic AI risk, governance and control frameworks: 2+ years Soft Skills Executive communication and presentation skills Strategic thinking and business outcome orientation Consultative stakeholder management Strong problem-solving and analytical abilities Influencing and decision-making without direct authority Cross-functional collaboration and leadership Mentoring and team enablement Ability to simplify complex technical concepts What Success Looks Like (First 6-12 Months) Enterprise AI roadmap approved and aligned with business priorities Vertex AI reference architecture established and adopted AI governance and security framework implemented Reusable Agentic AI architecture patterns defined Multiple AI use cases moved from concept to production SAP integration framework established for AI-enabled workflows Platform adoption increased across business units Architecture review and AI delivery governance process operational Measurable improvements in delivery speed, reuse, and risk management Strong executive confidence in AI platform strategy and execution
Why Join Us
Lead AI transformation for a global enterprise customer Shape the long-term AI and Agentic AI strategy Work directly with executive stakeholders and business leaders Architect cutting-edge solutions using Vertex AI and Google Cloud Drive high-impact SAP and enterprise AI innovation initiatives Establish enterprise standards and reusable AI platforms Influence technology decisions with organization-wide impact Be at the forefront of production-grade Agentic AI adoption