About the Client
Oliver James has partnered with a fast-growing, cloud-first European SaaS scale-up currently navigating the second phase of its internal AI transformation. Moving from decentralised pilots to a secure, enterprise-wide adoption model, their Internal IT and Data teams are bringing in a hands-on Internal AI & Governance Expert to bridge strategy, hands-on development, and change management.
Note: This role focuses exclusively on internal workflow optimisation, SaaS integrations, and internal web applications – no customer data or core product development involved.
Key Responsibilities
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Governance & Ways of Working: Refine internal AI governance frameworks, security standards, and development analytics suited for a regulated QMS environment.
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Business Challenge & ROI: Actively engage cross-functional stakeholders to interrogate the business logic and clear ROI behind requested AI tools before implementation.
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Hands-on Integration & Development: Partner closely with internal IT and Data teams to build and integrate AI capabilities into internal web applications using Python, TypeScript, and Git.
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Cloud Infrastructure: Leverage Azure AI tools (Azure OpenAI Service, Azure AI Search, Azure AI Foundry, Machine Learning) to deploy secure internal automation.
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Enablement & Knowledge Transfer: Demystify AI tools and technical concepts for non-technical teams, passing down practical knowledge to support adoption without line-management responsibilities.
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Program Support: Support key 2026 roadmap initiatives, including internal AI Knowledge Bases, AI Champions programs, and role-specific training modules.
Candidate Profile
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Governance & Adoption Strategy: Proven background scaling AI governance, data safety, and operational frameworks within SaaS or cloud-first setups.
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Technical Stack: Strong hands-on coding skills in Python and TypeScript, proficiency with Git, and direct experience building with Azure AI infrastructure.
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Web App Integration: Demonstrated experience integrating AI capabilities into web platforms alongside internal IT/Data engineering teams.
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Stakeholder Engagement: Confident challenging business requests, defining clear ROI, and translating technical architectures into plain language.
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Regulated/QMS Exposure: Previous exposure to regulated, quality-driven, or compliance-heavy environments is highly preferred.
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Fluency: Full professional proficiency in English.
