AI Platform Engineer / Architect

We are looking for an experienced AI Platform Engineer / Architect to take ownership of the architecture, deployment, and adaptation of an enterprise-grade agentic AI platform within a European cloud and enterprise environment.

You will be responsible for defining and maintaining the platform architecture, ensuring secure and compliant deployment, and acting as a key technical interface between application teams, IT infrastructure, and distributed platform engineering teams.

Key Responsibilities

Platform Architecture & Adaptation

Own the reference architecture for:Agent runtimeModel gatewayConnector and tooling frameworkSDK layerAdapt shared AI platform components for European deployment and compliance requirements.Define and maintain Architecture Decision Records (ADRs).Participate in architecture reviews and ensure compatibility with the broader platform roadmap.Identify and manage architectural dependencies and breaking changes.

Cloud Deployment & IT Integration

Deploy and operate platform services on approved cloud infrastructure in collaboration with Cloud/DevOps and IT teams.Own technical aspects of infrastructure and operational requirements, including:ProvisioningIAMNetworkingIncident escalationEnsure compliance with data residency, data retention, and cross-border data-transfer requirements.Integrate AI platform services with enterprise systems, identity providers, internal APIs, and document/data platforms.

Data & Knowledge Integration

Define secure connector patterns for:Vector searchEnterprise searchKnowledge graphsBig Data and Knowledge Database servicesWork closely with Data and Knowledge Engineering teams to ensure retrieval quality and appropriate access controls.

Technical Leadership & Enablement

Develop reusable architecture patterns, SDKs, and integration approaches.Establish build-versus-adapt-versus-reuse principles for AI use cases.Conduct architecture reviews for application teams.Mentor and support application engineers with platform integration challenges.

Required Qualifications

5+ years of experience in software, cloud, or platform architecture.2+ years of hands-on experience with LLM/agent platforms, RAG, or production AI services.Strong Python and/or TypeScript development skills.Strong experience with API design and distributed systems.Cloud-native engineering experience with:KubernetesCI/CDInfrastructure-as-CodeObservabilityGood understanding of:IAMNetworkingSecrets managementSecure API designPractical understanding of LLM and agent technologies, including:Model inferenceTool callingEmbeddingsVector searchAI evaluationGuardrailsComfortable working across distributed and multicultural engineering teams.

Preferred Qualifications

Experience designing GDPR-aware architectures and working with EU data-residency requirements.Knowledge of EU AI Act implications, including risk classification, logging, and auditing.Experience within automotive, mobility, manufacturing, or other enterprise environments.Familiarity with technologies such as:LangChain / LangGraphSemantic KernelTerraformArgoCDOpenTelemetryOr equivalent technologies Technical Environment

KubernetesAzure / AWS / GCPCI/CD pipelinesInfrastructure-as-CodeTerraform or equivalentOpenTelemetry or equivalent observability toolsPython / TypeScriptSecure API designIdentity & Access Management systems