AI Platform Architect

Quick Facts

AI Platform Architect responsible for designing and integrating a local enterprise AI platform.

Description

Design and architect the local AI Platform in the organization’s technology environment, ensuring secure and consistent integration with the broader enterprise architecture. Translate group reference architecture and platform standards into a local implementation model, identifying requirements, dependencies, and constraints. Provide architectural support for teams building AI/agent solutions and conduct architecture/design reviews to ensure correct platform usage.

Responsibilities

• Own local AI Platform architecture and ensure secure, consistent embedding in the local enterprise architecture.
• Convert group architecture, standards, and platform capabilities into local implementation and usage.
• Design and align integrations between the AI Platform and local systems, services, data, network, IAM, monitoring, and other infrastructure components.
• Identify local architectural requirements, dependencies, and constraints and assess their impact on platform evolution.
• Support design of new and expansion of existing AI Platform capabilities.
• Ensure scalability, reliability, and coherent evolution of the platform as AI solutions grow.
• Apply Security by Design: IAM/service identities, secrets management, network isolation/private connectivity, API security, data protection, and auditability.
• Identify AI/agent-specific security risks and collaborate closely with an AI Security Engineer.
• Support solution teams with platform-based architecture patterns for models, AI Gateway, RAG, Context Engineering, Tool Calling, agent orchestration, API integration, identity, observability, and Human-in-the-Loop.
• Verify solutions from integration, data flow, permissions, scalability, resilience, and security perspectives.
• Recommend approaches when use-case needs exceed current platform capabilities.
• Manage architectural dependencies between the AI Platform and local/group components; maintain local architecture patterns.
• Identify and coordinate deviations from standard architecture; document key decisions and agreed deviations.
• Coordinate with central group architects and analyze new centrally delivered capabilities for local embedding.

Requirements

• Minimum 3 years of experience as a Platform Architect, Cloud Architect, Solution Architect, or similar senior architecture role.
• Very good knowledge of cloud solution architecture, especially Microsoft Azure.
• Experience designing technology platforms and integrating them into complex enterprise environments.
• Strong understanding of GenAI and Agentic AI architecture (LLMs, AI Gateway, RAG, Context Engineering, Tool Calling, agent orchestration, Human-in-the-Loop, evaluation, observability).
• Very good knowledge of integration architecture including APIs, containerization, and system communication patterns.
• Practical Cloud Security and Security Architecture knowledge—especially IAM and Least Privilege, Microsoft Entra ID, OAuth2/OIDC, service/managed identities, secrets management, network segmentation/private connectivity, TLS and API Security, data protection, logging, monitoring, and auditability.
• Understanding of AI/agent risks such as excessive permissions, agent access to tools/systems, data leakage, and prompt injection.
• Experience conducting architecture/design reviews and documenting architecture decisions.
• Ability to identify and manage dependencies and analyze trade-offs between use-case requirements and platform capabilities.
• Ability to collaborate with development, Security, Cloud, Network, Data, and Enterprise Architecture teams.
• Very good English for daily collaboration with group teams.
• Experience in AI Platform / GenAI / Agentic AI architecture.
• Knowledge of tools and platforms such as Azure AI Foundry, Azure AI Services, Azure Container Apps or Kubernetes, API Management/AI Gateway, RAG, semantic search and vector databases, LangGraph/LangChain, Model Context Protocol (MCP), Microsoft Entra ID/OAuth2/OIDC, Terraform/Infrastructure as Code, OpenTelemetry/MLflow.

Benefits

• Challenging work and collaboration with experienced IT professionals.
• Opportunity to contribute to the rollout and development of a new group AI platform.
• Ownership and real influence on the direction of transformation.
• Access to latest IT technologies.
• Enterprise-stable environment and a values-driven culture (community, simplicity, client focus, responsibility, credibility).