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

• Design end-to-end AI solution architectures using Azure AI Foundry, AWS Bedrock, and Google Vertex AI to address specific business challenges.
• Define and maintain AI reference architectures and design patterns for common use cases including document intelligence, conversational AI, knowledge mining, and process automation.
  
• Build and maintain the AI Managed Services portfolio, defining service offerings, SLAs, and operational procedures.
  
• Develop reusable accelerators, templates, and tooling to streamline AI solution delivery across engagements.
  
• Create Professional Services engagement frameworks, scoping templates, and delivery methodologies for AI projects.
  
• Hands-on development of proof-of-concepts and prototypes to validate AI solution approaches with customers.
  
• Define and implement AI solution lifecycle management including monitoring, model evaluation, retraining, and continuous improvement.
  
• Monitor the rapidly evolving AI landscape, evaluating new services, tools, and frameworks across Azure, AWS, for applicability to the services portfolio.
  
• Collaborate with Cloud and Data Product Architects to ensure integrated solution design across the broader product portfolio.
  
• Guide and mentor engineering teams on AI solution design, and develop internal training materials and knowledge-sharing sessions on AI technologies.
  

• Demonstrable background in designing and delivering AI/ML solutions using cloud platforms, with strong experience in Azure AI Foundry, Azure OpenAI Service, Azure AI Search, Copilot Studio, and Azure AI Document Intelligence.
  
• Working knowledge of AWS Bedrock/SageMaker, with experience designing RAG architectures and AI orchestration patterns (Semantic Kernel, AutoGen, Microsoft Agent Framework, LangChain).
  
• Experience integrating AI into applications and creating AI enable applications.
  
• Strong communication and collaboration skills, with the ability to explain complex AI concepts to non-technical stakeholders and support pre-sales engagements.
  
• Understanding of responsible AI principles, prompt engineering, model evaluation, and proficiency with Infrastructure as Code (Terraform, Bicep) for AI workload deployments.
  
• Experience in a professional services, consulting, or managed services environment, with a demonstrable portfolio of AI solutions delivered for business use cases.
  
• Familiarity with Microsoft Well-Architected Framework and Azure Landing Zones.
  
• 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.