AI Platform Engineer / Architect

📍 Gothenburg, Sweden (Hybrid) - Contract

✈️ International Travel Required (China up to 4 times per year, approximately 1 week per trip)

Shape the Future of Enterprise AI

Our client is seeking an experienced EU AI Platform Engineer / Architect to play a pivotal role in the deployment and evolution of a next-generation agentic AI platform within Europe.

This is a unique opportunity to act as the technical bridge between European application teams, European IT infrastructure, and China-based platform engineering teams. You will own the EU-side architecture, ensure secure and compliant deployments, and help establish the foundation for enterprise-scale AI solutions across the organisation.

What You'll Be Doing

Platform Architecture & AI Enablement

• Own and evolve the EU reference architecture for:
  • Agent runtime environments
  • Model gateways
  • Connector and tooling frameworks
  • SDK and developer experience layers
• Adapt shared AI platform components developed by China R&D for EU deployment requirements.
• Define and maintain Architecture Decision Records (ADRs) where regional requirements differ.
• Participate in China-EU architecture reviews, influencing platform compatibility, roadmap alignment, and technical decision-making.
• Provide reusable AI platform patterns and guidance to application development teams.

Cloud Platform & Enterprise Integration

• Deploy and operate AI platform services within approved EU cloud environments.
• Work closely with Cloud Engineering, Dev Ops, and IT teams on:
  • Infrastructure provisioning
  • Identity and access management
  • Network architecture
  • Incident management and escalation processes
• Ensure compliance with EU data residency, retention, and cross-border transfer requirements.
• Integrate platform services with enterprise systems including identity providers, APIs, and data platforms.

Data & Knowledge Services

• Design secure integrations with:
  • Vector databases
  • Enterprise search platforms
  • Knowledge graph solutions
• Collaborate with Data and Knowledge Engineering teams to improve retrieval quality, governance, and access controls.

Technical Leadership

• Mentor engineers and support application teams integrating with the platform.
• Drive adoption of a build-adapt-reuse framework across AI initiatives.
• Promote platform thinking and reusable architecture patterns instead of one-off implementations.

What We're Looking For

Essential Skills & Experience

• 5+ years' experience in software architecture, cloud architecture, or platform engineering.
• 2+ years of hands-on experience with:
  • LLM platforms
  • Agent-based AI systems
  • RAG architectures
  • Production AI services
• Strong development skills in Python and/or TypeScript.
• Solid experience designing APIs and distributed systems.
• Cloud-native expertise including Kubernetes, CI/CD, Infrastructure as Code, and observability.
• Strong understanding of IAM, secure API design, networking, and secrets management.
• Practical knowledge of AI concepts including inference, tool calling, embeddings, vector search, evaluation frameworks, and guardrails.
• Experience collaborating across international and multicultural engineering teams.

Preferred Experience

• GDPR-compliant architecture design.
• Understanding of EU AI Act requirements, including auditability and logging.
• Automotive, mobility, or manufacturing industry experience.
• Experience with technologies such as LangChain, LangGraph, Semantic Kernel, Terraform, ArgoCD, and OpenTelemetry.

Personal Attributes

• Strong drive to take on new challenges.
• Adaptable and comfortable in evolving environments.
• Collaborative and team-oriented.
• Open-minded, inclusive, and solution-focused.
• Strong communication skills with the ability to bridge technical teams across Europe and China.

Why Join?

This is an opportunity to help shape the future AI platform strategy for our client, working at the forefront of enterprise AI, cloud architecture, and international collaboration. You will have significant influence on technical decisions, architecture direction, and the adoption of AI solutions at scale.

Interested? We'd love to hear from you.