Quick overview
Job description
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
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