AI Architect (Enterprise AI)

We are looking for an experienced AI Architect to join a forward-thinking global digital organization, reporting directly to senior leadership within Digital Futures.
In this role, you will define and drive the enterprise AI strategy across complex data ecosystems and platforms such as SAP, Salesforce, Microsoft 365 Copilot, and internal systems. You will work closely with global business and technology teams to identify high-impact AI use cases, architect intelligent solutions, and lead enterprise-wide adoption.
This is a high-visibility role where you will shape next-generation AI capabilities and influence how AI transforms both customer experience and internal operations across a global organization.
Key Responsibilities
Enterprise AI Strategy & Architecture
Define and implement enterprise-wide AI architecture aligned with business strategy
Identify and prioritize high-value AI use cases and develop business cases
Establish governance, standards, and best practices for AI adoption
Monitor market trends and emerging AI technologies to guide strategic direction
AI Architecture Leadership
Design scalable, secure, and compliant AI architectures
Lead architecture decisions for complex AI systems and enterprise integrations
Define principles for AI solution design, deployment, and lifecycle management
Ensure consistency, quality, and long-term sustainability of AI platforms
AI Solutions & Transformation
Architect and guide development of AI agents, copilots, and intelligent workflows
Enable integration with enterprise platforms (SAP, Salesforce, Microsoft 365, etc.)
Drive AI adoption across business units and coach cross-functional teams
Establish KPIs/OKRs and measure performance of AI initiatives
Core Competencies
AI Strategy & Innovation – Defining roadmaps and identifying impactful use cases
Enterprise AI Architecture – Agent frameworks, RAG pipelines, and integrations
AI Solution Delivery – End-to-end design and implementation
Leadership & Influence – Driving adoption and aligning stakeholders
Performance Management – Measuring impact and optimizing outcomes
Skills & Expertise
Technical
Azure AI / OpenAI services (or equivalent cloud AI platforms)
MLOps, model lifecycle management, and deployment
Data engineering (ETL/ELT, distributed systems)
API integrations and cloud-native architectures
Secure and responsible AI engineering practices
Multi-agent systems, orchestration frameworks, and GenAI solutions
Architecture
Enterprise architecture across data, application, and platform layers
Scalable and secure system design
Knowledge of AI-enhanced architecture patterns
Knowledge graphs, digital twins, and capability mapping
Governance & Security
Responsible AI and compliance frameworks
Data governance, access control, and lineage
AI safety, guardrails, and risk mitigation
Experience Required
Proven experience designing large-scale distributed systems
Strong background in AI/ML solution architecture and deployment
Experience integrating AI into enterprise platforms like SAP, Salesforce, Microsoft 365
Exposure to AI-driven modernization of legacy systems
Experience across enterprise architecture, cloud, APIs, and microservices
Education:
Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field
Why Join
Competitive compensation and strong recognition culture
Remote-first / Work-from-anywhere flexibility (Europe)
Opportunity to shape enterprise-level AI transformation
Work with global teams on cutting-edge AI initiatives
Strong focus on innovation, learning, and career growth

Work arrangement
Yes