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Enterprise Architect

Envision LLC.United States🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeRemote
LocationUnited States
Stakeholder ManagementGoogle CloudLLMPythonGenerative AIRESTCI/CDIAM

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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