Workplace AI Architect

Sulzer is a leading engineering company with a proud heritage of innovation. Join our global team to grow your expertise and develop innovative solutions that enable a prosperous and more sustainable society.

Define and govern the adoption of AI across Workplace and platform-based solutions with a strong focus on out-of-the-box capabilities integrations and security. Act as the orchestration point across Software Development Data & Analytics business users and platform owners ensuring consistent routing of AI initiatives. Drive the transition from ad-hoc usage to controlled scalable adoption through clear governance measurement and chargeback positioning AI as an extension of existing platforms rather than a parallel capability. The role focuses on Workplace AI platforms and embedded capabilities such as Microsoft 365 Copilot AI assistants and collaboration tools.

Main accountabilities and tasks

• AI Roadmap & Out-of-the-Box Ownership: Own the AI roadmap for Workplace and platform-based AI capabilities and the adoption of out-of-the-box solutions; contribute to the cross-functional definition of AI architecture; establish AI as a coherent enterprise capability.
• Platform-First Preview & Early-Access Ownership: Prioritise out-of-the-box capabilities over new builds; own the evaluation piloting and rollout of preview features and vendor early-access programmes; track and govern AI features increasingly embedded in existing enterprise services.
• Governance of Services Integrations & Agents: Establish a single enterprise entry point and a risk-based approval process supported by self-service guardrails and clear approval timelines so the front door enables rather than blocks; govern AI services integrations APIs and the lifecycle of AI agents; ensure every AI asset is inventoried owned and operated within agreed controls.
• Routing of AI Initiatives Across Delivery Tracks: Define and govern how AI initiatives are routed across delivery tracks - out-of-the-box preview and early-access (this role); citizen development (business users against standards set by this role); custom development and advanced integrations (Software Development); and analytics-driven solutions (Data & Analytics).
• Security Risk & Compliance (with Infosec): Together with Infosec define and enforce AI-specific controls under a clear split of accountability for who defines approves and enforces; ensure compliance with GDPR and the EU AI Act; govern third-party AI usage and minimise shadow-AI risk.
• AI Lifecycle Management: Govern the full lifecycle covering build publish operate and retire; ensure ownership inventory and transparency for every AI solution; enforce environment-based controls across experiment managed and production.
• Business Value Chargeback & Adoption: Define how AI business value is measured; build and operate a chargeback model so consumption is transparent and costs sit with the consuming business; drive adoption and track it against value realisation.
• User Support Enablement & Training: Act as the primary point of contact for AI adoption; provide patterns guardrails and reusable templates so users can build safely; deliver training documentation and onboarding paths that build AI literacy across the organisation.

Desired experience and qualifications

• Work experience: 8-10 years in enterprise IT architecture or transformation roles with experience in governance platform strategy or large-scale adoption.
• Expertise: Senior expert / enterprise architect level. Strong understanding of enterprise AI platforms (e.g. Microsoft 365 Copilot) and assistant and agent-based tooling and of GenAI / agent-based architectures; deep knowledge of platform vs. custom-development trade-offs and licensing models; experience defining operating models and governance standards.
• Governance & regulation: Proven experience defining and rolling out enterprise AI governance frameworks or platform-adoption strategies; familiarity with AI security controls and applicable regulation (EU AI Act GDPR responsible-AI guidance).
• Cloud & FinOps: Deep familiarity with cloud platforms (Microsoft ecosystem preferred); familiarity with chargeback or FinOps models ideally applied to AI or cloud services; working knowledge of enterprise AI licensing and the ability to translate licensing constraints into platform and routing decisions.
• Education & certifications: University degree in IT Computer Science or a related field; Microsoft AI or cloud certifications preferred with security and compliance certifications a plus.
• Soft skills: Strategic and structured thinking; clear pragmatic communication including the ability to translate technical standards for business users and citizen developers; sound decision-making in complex ambiguous environments; comfort balancing innovation with control.
• Languages: Fluent English required; additional languages a plus.
  

Medical insurance for self and family

Company sponsored transportation facility

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