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Google AI Architect
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Google AI Architect – Gemini Enterprise | Agentic AI Transformation
We are looking for an experienced Google AI Architect to lead the architecture, design, and implementation of an enterprise-wide Agentic AI Transformation Programme.
The role will focus on shaping the target AI architecture using Google Gemini Enterprise, Vertex AI, Agent Engine, Agentspace, NotebookLM, RAG, Knowledge Graphs, and enterprise integrations to deliver scalable AI assistants, autonomous agents, and AI-driven business process automation. Potential opportunity for permanent employment following the initial 6-month contract, subject to performance and business requirements.
Key Responsibilities
AI Strategy & Enterprise Architecture
- Define the enterprise Agentic AI architecture, roadmap, standards, and governance frameworks.
- Establish reusable reference architectures and design principles for enterprise AI adoption.
- Lead architecture decisions across Gemini Enterprise, Vertex AI, Agent Engine, Agentspace, NotebookLM, RAG, Multi-Agent systems, and Knowledge Graphs.
- Drive the adoption of reusable AI capabilities and enterprise platforms rather than isolated point solutions.
Agentic AI Solution Design
- Design enterprise AI assistants and autonomous agents across areas such as Operations, Asset Management, Engineering, Finance, Procurement, Customer Services, and Knowledge Management.
- Define agent orchestration patterns including Supervisor, Planner, Task, Workflow, and Human-in-the-Loop agents.
- Design scalable multi-agent frameworks using Google Agent Development Kit (ADK) and Agent Engine.
- Establish patterns for tool calling, workflow automation, agent observability, and governance.
Data & Knowledge Architecture
- Define enterprise knowledge architecture for AI grounding and contextual intelligence.
- Architect RAG solutions using Gemini Enterprise Search, Vertex AI Search, SharePoint, Confluence, GCS, and enterprise document repositories.
- Define semantic models, metadata standards, ontologies, and Knowledge Graph integration patterns.
- Ensure data quality, lineage, governance, security, and discoverability.
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Platform & Enterprise Integration
- Define AI integration architecture across SAP, ServiceNow, Microsoft 365, SharePoint, HR systems, and operational platforms.
- Leverage Apigee, Application Integration, APIs, event-driven architectures, and MCP interfaces.
- Establish enterprise standards for integrating AI capabilities into business processes.
Security, Governance & Responsible AI
- Design secure and governed Agentic AI frameworks aligned with enterprise security requirements.
- Work with IAM, VPC Service Controls, Model Armor, Security Command Center, and Responsible AI guardrails.
- Establish governance covering prompt management, model lifecycle, agent lifecycle, data privacy, regulatory compliance, auditability, and explainability.
Architecture & Delivery Leadership
- Provide technical leadership to AI Engineers, Data Engineers, Developers, and Platform Architects.
- Review solution designs and ensure alignment with enterprise architecture standards.
- Lead architecture boards, design reviews, technical workshops, and senior stakeholder discussions.
- Support AI business cases, transformation initiatives, and value-realisation activities.
Essential Experience
- 12+ years of enterprise architecture experience.
- 5+ years of experience in AI/ML, Generative AI, and/or AI architecture.
- Strong enterprise experience with Google Cloud Platform (GCP).
- Proven expertise with Vertex AI, Gemini Enterprise, and Agentic AI platforms.
- Experience delivering enterprise-scale AI transformation programmes.
- Hands-on experience designing:
- RAG architectures
- Multi-agent systems
- LLM-powered applications
- Enterprise AI platforms
- Strong understanding of data architecture, knowledge management, ontologies, semantic layers, and knowledge graphs.
- Experience working with senior business, technology, and architecture stakeholders.
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Google Cloud & AI Platform Skills
- Strong experience with several of the following:
- Gemini Enterprise
- Vertex AI
- Agent Engine
- Gemini API
- Vertex AI Search
- Vertex AI Studio
- Agentspace
- NotebookLM Enterprise
- BigQuery
- Cloud Run
- GKE
- Apigee
- IAM
- VPC Service Controls
- Security Command Center
Agentic AI Skills
- Multi-Agent Architecture & Design Patterns
- Agent Orchestration
- AI Workflow Automation
- Prompt Engineering
- Tool Calling
- MCP Frameworks
- Google Agent Development Kit (ADK)
- Human-in-the-Loop (HITL) Architecture
- AI/Agent Observability
- Agent Governance
Preferred Experience
- Experience within Utilities, Energy, Power Generation, or Trading.
- Experience delivering large-scale business transformation programmes.
- Experience with Knowledge Graphs, Semantic Layers, and Enterprise Search.
- Exposure to Operational Technology (OT) and asset-intensive environments.
- Experience establishing AI operating models and governance frameworks.
Education & Certifications
Mandatory
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related discipline.
Preferred
- Google Professional Cloud Architect
- Google Professional Machine Learning Engineer
- Professional Agentic Architect
- TOGAF
- SAFe Architect
What We're Looking For
We are looking for an architect who can operate at both strategic and technical levels — someone who can define the enterprise Agentic AI vision and architecture while also working closely with engineering teams to turn that vision into scalable, secure, and production-ready AI solutions.
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