Product Architect

Why SCC?

• An inclusive workplace
• Excellent package: solid basic and company benefits
• Hybrid working & core hours in line with role requirements
• Career development and life-long learning opportunities
• Opportunity to join Europe's largest privately-owned IT Company

• Build and maintain the AI Managed Services portfolio, defining service offerings, SLAs, and operational procedures.
  
• Define and implement AI solution lifecycle management tooling including monitoring, model evaluation, retraining, and continuous improvement.
  
• Integrate services and tooling with existing SCC tools and workflow.
  
• Make and defend build vs buy decisions, weighing hyperscale-native services, third-party tooling and in-house build.
  
• Develop reusable accelerators, templates, and tooling to streamline AI solution delivery across Professional Services engagements.
  
• Create reference architectures and design patterns for common AI use cases including GenAI, agentic workflows, document intelligence, conversational AI, knowledge mining and process automation.
  
• Collaborate with Cloud and Data Product Architects to ensure integrated solution design across the broader product portfolio.
  
• Collaborate with other Product Architects and Engineers to ensure solutions integration with existing services, tools and processes.
  
• Monitor the rapidly evolving AI landscape, evaluating new services, tools, and frameworks across Azure, AWS, for applicability to the services portfolio.
  
• Guide and mentor engineering teams on AI solution design and develop internal training materials and knowledge-sharing sessions on AI technologies.
  
• Contribute to thought leadership through blog posts, whitepapers and customer workshops
  

• Strong experience of the Microsoft AI stack for building business AI solutions: Azure AI Foundry, Azure OpenAI Service, Azure AI Search, Copilot Studio, and Azure AI Document Intelligence.
  
• Awareness of the wider Microsoft stack; Azure Landing Zones, App hosting services, Sentinel, Purview, Fabric, Well-Architected Reviews, etc.  
  
• Working knowledge of AWS Bedrock/SageMaker, with experience designing RAG architectures and AI orchestration patterns (Semantic Kernel, AutoGen, Microsoft Agent Framework, LangChain).
  
• Familiarity with data engineering fundamentals and data platform integration.
  
• Experience implementing identity and access patterns for AI workloads (Entra ID, managed identities, service principals for agents).
  
• Understanding of AI governance and compliance frameworks (for example EU AI Act, ISO 42001, NIST AI RMF), responsible AI principles, prompt engineering and model evaluation.
  
• Proficiency with Infrastructure as Code (Terraform, Bicep).
  
• Experience in a pro services, consulting, or managed services environment, with a demonstrable portfolio of AI solutions delivered for business use cases.
  
• Strong communication and collaboration skills, with the ability to explain complex AI concepts to non-technical stakeholders.
  
• Ability to work autonomously with an organised and results-oriented approach.
  
• Preferred certifications: Azure AI Engineer Associate (AI-102), Azure Solutions Architect Expert (AZ-305), AWS Certified Machine Learning – Specialty, or Google Professional Machine Learning Engineer.
  
• Eligible for and willing to obtain SC (Security Check) clearance or equivalent.