Description

• Enterprise GenAI & AI Platform Architecture
• Own end-to-end Azure GenAI architecture, leveraging:
• Azure AI Foundry
• Azure OpenAI
• Azure AI Search (RAG patterns)
• Define reference architectures for:
• AI Knowledge Assistants
• Legal / HR / Finance AI use cases
• Multi tenant AI platforms and shared AI foundations
• Ensure architectural consistency across multiple AI initiatives.
• Agentic & Multi Agent System Design
• Design agentic orchestration patterns, including:
• Multi agent workflows
• Tool calling, function calling, prompt chaining
• Routing, fallback, confidence logic
• Define how frameworks such as:
• LangChain
• LangGraph
• LlamaIndex
• are used safely and consistently (guardrails, not experimentation).
• Security, Governance & Responsible AI
• Define enterprise grade controls for:
• Data segregation (PII / confidential / restricted)
• RBAC, Managed Identity, private networking
• Content filtering, grounding, and citation enforcement
• Ensure alignment with:
• AkzoNobel security & compliance standards
• Responsible AI and audit requirements
• Act as final technical authority on “what is allowed vs not allowed”.
• Azure & Enterprise Integration Architecture
• Define integration patterns with:
• Microsoft Teams / M365 / Graph API
• SAP, ServiceNow, other enterprise systems
• Azure API Management
• Review and approve:
• CI/CD approach (Azure DevOps)
• Network, private endpoints, and environment strategy
• Partner with Infra / Security architects — not replace them.
• Technical Leadership & Governance
• Act as technical decision maker across AI programs.
• Review designs from teams and vendors; approve or course correct.
• Mentor Senior Technical Leads on:
• Design patterns
• Non functional requirements
• Production readiness
• Support presales / solution shaping when needed (light touch).

Qualifications:
Required Skills & Experience

• 12+ years in architecture / senior technical leadership roles
• Strong experience with Microsoft Azure Cloud Architecture
• Deep understanding of:
  • GenAI / LLM based systems
• RAG, embeddings, grounding, hallucination controls
• Experience architecting secure, enterprise scale AI platforms
• Ability to translate business use cases into enforceable technical architecture

Good to Have

• Azure certifications (Architect / AI Engineer preferred)
• Experience defining:
• AI governance or Responsible AI frameworks
• Exposure to multi modal or advanced AI use cases
• Experience working with global enterprise stakeholders

Key Skills

Education

Bachelor's degree