[Hiring] Lead AI Platform Engineer @Lease a Bike Deutschland

Role Description

We are looking for a Lead AI Platform Engineer (m/f/d) to own the AI platform on AWS and Snowflake that data scientists, AI engineers, and business teams build on.

• Co-own the AI platform with the Head of Data & AI: architecture, roadmap, and decision-making on adoption, building, or buying.
• Be the hands-on technical lead to ensure ML and AI engineers can ship new models or agents quickly, safely, and transparently regarding costs.

Architecture & Infrastructure:

• Set standards for infrastructure, access, and deployment with IT, security, and ML & AI engineers.
• Build all AI platform components with Terraform on top of the AWS foundation and GitLab setup of our cloud engineering team.

LLM & AI Compute:

• Run AWS Bedrock as our model gateway (access, guardrails, quotas, cost per team).
• Scale SageMaker and GPU workloads, and decide when managed APIs are sufficient.

Pipelines & Enablement:

• Provide orchestration and CI/CD (e.g. Airflow, GitLab), integrated with Snowflake.
• Offer reusable components and self-service deployment to avoid rebuilding infrastructure for every project.

Evaluation & Observability:

• Provide teams with tracing, evaluation, monitoring, and cost per service for their models and agents.

Security & Governance:

• Implement least-privilege access, audit trails, and technical guardrails for responsible AI.
• Assist non-technical colleagues in using approved AI tools safely.

Team Building:

• Mentor junior colleagues and set engineering standards for the growing AI team.

Qualifications

• 6+ years in platform engineering, DevOps, cloud engineering, or MLOps, with platforms designed and run in production.
• Strong AWS skills, hands-on Terraform (or AWS CDK), and security built in from the start: access control, secrets, audit logging.
• Experience with CI/CD (e.g. GitLab CI), Docker, workflow orchestration (e.g. Airflow), and Snowflake or a comparable cloud data platform.
• Experience running ML and LLM workloads in production: managed model access (e.g. AWS Bedrock or comparable), guardrails, evaluation, and cost control.
• Ability to make defendable architecture decisions, guide other engineers, use AI coding tools daily, explain trade-offs to non-technical colleagues, and fluency in English.

Requirements

• Experience with MCP servers or other infrastructure for AI agents.
• Experience with Kubernetes and self-hosted model serving (e.g. vLLM).
• Working knowledge of GDPR and the EU AI Act.
• Conversational German or Dutch.

Benefits

• Subsidized bike lease and bike purchase.
• Equipped home office for comfortable work.
• Learning budget and conference days to support your growth.
• 100% remote work from anywhere in the EU, with regular team meetings in operating countries.