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 runtime
- Model gateway
- Connector and tooling framework
- SDK layer
- Adapt 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:
- Provisioning
- IAM
- Networking
- Incident escalation
- Ensure 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 search
- Enterprise search
- Knowledge graphs
- Big Data and Knowledge Database services
- Work 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:
- Kubernetes
- CI/CD
- Infrastructure-as-Code
- Observability
- Good understanding of:
- IAM
- Networking
- Secrets management
- Secure API design
- Practical understanding of LLM and agent technologies, including:
- Model inference
- Tool calling
- Embeddings
- Vector search
- AI evaluation
- Guardrails
- Comfortable 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 / LangGraph
- Semantic Kernel
- Terraform
- ArgoCD
- OpenTelemetry
- Or equivalent technologies
**Technical Environment**
- Kubernetes
- Azure / AWS / GCP
- CI/CD pipelines
- Infrastructure-as-Code
- Terraform or equivalent
- OpenTelemetry or equivalent observability tools
- Python / TypeScript
- Secure API design
- Identity & Access Management systems
