Lead AI Platform Engineer (m/f/d)

Lease a Bike Deutschland GmbH; United States; À distance; USD 160 000 - 240 000; Plein temps

Avantages offerts par ce poste

Bike lease subsidy

Home office equipment provided

Learning budget

Résumé du poste

Bike Mobility Services GmbH is seeking a Lead AI Platform Engineer (m/f/d) to own and shape the AI platform on AWS and Snowflake. You will co-own the architecture with the Head of Data & AI and lead hands-on implementation to enable ML engineers to ship models quickly, safely, and cost-effectively.

You will define standards, scale compute, and build reusable components with Terraform and GitLab. The role is 100% remote within the EU, with collaboration across teams and ongoing mentoring of

Qualifications

• 6+ years in platform engineering, DevOps, cloud engineering, or MLOps, with production systems in mind.
• Strong AWS skills with Terraform or AWS CDK, plus security by design: access control, secrets, audit logging.
• CI/CD with GitLab CI, Docker, workflow orchestration (Airflow); Snowflake or equivalent cloud data platform.
• Experience running ML/LLM workloads in production with guardrails, evaluation, and cost control.
• Ability to own architecture decisions, mentor engineers, and communicate trade-offs to non-technical stakeholders; fluent in English.

Responsabilités

• Architect and set standards for infrastructure, access, and deployment with IT, security, and ML/AI teams.
• Run AWS Bedrock, scale SageMaker/GPU workloads, decide when managed APIs suffice.
• Provide orchestration and CI/CD (Airflow, GitLab), integrated with Snowflake; reusable components and self-service deployment.
• Provide tracing, evaluation, monitoring, and cost per service for models and agents.

Connaissances

Platform engineering

DevOps

Cloud engineering

MLOps

English fluency

Outils

Terraform

AWS CDK

GitLab

Airflow

Snowflake

Docker

Kubernetes

Description du poste

Decide How AI Gets Built at a Fast-Growing Bike Leasing Company.

Do you want to decide what an AI platform looks like, and care as much about guardrails, evaluation, and cost as about getting the first model deployed?

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.

Who are we

Bike Mobility Services GmbH, a subsidiary of the Dutch company Pon.Bike , is part of a group that owns international brands like Kalkhoff, Cervélo, Urban Arrow, Cannondale, Santa Cruz, Focus, and Royal Dutch Gazelle. Our mission is to get as many employees as possible onto bikes for their commute, through our digital Lease a Bike portal. Data already drives how we steer our portfolio and manage residual values. Now we are building the platform that puts AI into those processes.

Your Mission

You co-own the AI platform with the Head of Data & AI: architecture, roadmap, and the decision what we adopt, build, or buy. You are the hands-on technical lead. Your goal is that ML and AI engineers ship a new model or agent in days, safely and with costs they can see.

Core Responsibilities:

• - Architecture & Infrastructure: Set standards for infrastructure, access, and deployment with IT, security, and the 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 enough.
• - Pipelines & Enablement: Provide orchestration and CI/CD (e.g. Airflow, GitLab), integrated with Snowflake, plus reusable components and self-service deployment, so teams do not rebuild infrastructure for every project.
• - Evaluation & Observability: Give teams tracing, evaluation, monitoring, and cost per service for their models and agents, so they can track quality and spend on their own.
• - Security & Governance: Implement least-privilege access, audit trails, and technical guardrails for responsible AI. Help non-technical colleagues use approved AI tools safely.
• - Team Building: Mentor more junior colleagues and set the engineering standards of the AI team as it grows.

What You Bring

Must-Haves:

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

Nice-to-Haves:

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

Why Join?

• - Real Impact: You decide architecture and roadmap, and what you build in the first year becomes the standard for the AI team.
• - Close to the Use Cases: Direct access to the teams behind concrete projects in traditional and agentic AI.
• - Bike Leasing & Home Office: We subsidize your bike lease and bike purchase, and we equip your home office so you can work comfortably.
• - Learning: You get a learning budget and conference days to grow where you want.
• - 100% Remote: You work from anywhere in the EU, and we meet regularly as a team in one of our operating countries, so you get to know the people behind the use cases.