AI Solution Architect

About the role

The AI Solution Architect defines and governs HOYA's common AI layer, the shared foundation on which divisions adopt machine learning, generative AI, copilots and agentic solutions securely, responsibly and at scale. The role turns business strategy, risk requirements and technology opportunities into architecture principles, platform guardrails, reference designs and reusable patterns, and leads architecture assurance for priority solutions.

Key responsibilities

• Collaborate with Enterprise Architecture to maintain the enterprise AI target architecture, principles, standards, roadmap and reference patterns.
• Translate business, data, security, privacy, legal, regulatory and responsible AI requirements into enforceable guardrails and design controls.
• Define reference architectures for predictive ML, generative AI, RAG, copilots, agents and multi-agent orchestration.
• Architect the Azure AI ecosystem and define end-to-end MLOps and LLMOps, including evaluation, CI/CD, release, rollback, monitoring and retraining.
• Set enterprise evaluation standards for quality, accuracy, bias, safety, latency, cost and business outcomes.
• Define secure RAG and agentic patterns, and governance patterns for identity, authorization, memory, tools, actions, human oversight and audit trails.
• Apply Agent Security Posture Management to agent inventory, permissions, data access, tool usage and risk remediation.
• Lead architecture reviews, document decisions and risks, and approve production readiness.
• Guide technology selection, build-versus-buy decisions and vendor assessment, and partner with engineers and division teams on proofs of concept.

Required profile

• Bachelor's degree in computer science, AI, data science, engineering or a related field.
• At least 10 years of solution or enterprise architecture experience, including significant AI, machine learning or advanced analytics architecture responsibility.
• Ability to influence executives and senior technical stakeholders and to govern cross-division designs.
• Microsoft certifications such as Azure Solutions Architect Expert, Azure AI Engineer Associate or Azure Data Scientist Associate; TOGAF is beneficial.
• Experience establishing an enterprise AI platform or leading AI architecture in a federated global organization is preferred.

Required skills

• Azure AI Foundry, Azure OpenAI, Azure Machine Learning, Azure AI Search, Microsoft Fabric and integration services.
• ML, generative AI, RAG, embeddings, vector search, agentic architecture and orchestration.
• MLOps/LLMOps, evaluation, CI/CD, monitoring, drift and incident response.
• AI security, responsible AI, privacy, identity, Zero Trust, threat modelling and secure software development.
• APIs, event-driven architecture and data/knowledge architectures.
• Preferred: Copilot Studio, Power Platform, Agent Security Posture Management and AI observability.