Senior Forward Deployed Platform Engineer (m/w/d)

Here's how we picture you as our Senior Forward Deployed Platform Engineer:

These are the knowledge and skills you need:

• Experience with AWS (CloudFormation, IAM, ECR, SageMaker, Bedrock, S3, SQS, DynamoDB, RDS, KMS).
• Experience with Kubernetes (EKS) in production (kustomize, HPA and KEDA based autoscaling).
• Experience deploying SageMaker models, setting up custom inference containers (HuggingFace and/or OSS model) and endpoints (provisioning, autoscaling, and blue/green rollouts).
• Familiarity with observability & LLMOps best practices and solutions (Datadog, Langfuse, LLM/GenAI tracing, OTel, CloudWatch).
• Proficiency in Python, specifically with FastAPI and async task management.
• Knowing how to set up ML/LLM GPU inference on EKS (GPU-backed instances, Nvidia driver/plugin).
• Ability to own technical decisions and collaborate directly with other teams.
• Troubleshooting, RCA, and resolving problems. When things get stressful, you stay cool headed and work through issues step by step, asking for support from SMEs when needed.
• Preference for writing over talking, resulting in clear, concise, yet complete documentation and asynchronous communications.
• This is a cross-functional role bridging the gap between applications and the platform. Ability to both explain complex concepts clearly to non-domain experts, and extract information through well-formed questions during verbal communication, is a must.

Bonus points:

• Healthcare or regulated-domain experience (e.g. ISO 27001, C5).
• Self-hosting/home lab.
• Nvidia Triton/vLLM or similar.
• MLflow, Kubeflow, ClearML, DVC, Vertex AI.
• Slack and GitHub automations (bots, workflows, apps, etc.).

This will help you decide if you want to join us – our values are:

• Strong opinions, weakly held. We adapt, negotiate trade-offs, and reconsider decisions when necessary. We don't stick to one implementation – we re-evaluate and adjust as needed (including throwing away the old one).
• Pragmatic choice of tools and avoidance of one-size-fits-all thinking.
• Bringing professionalism and empathy to how you work with others.
• Strong belief in solid technical fundamentals and preference for understanding and first principles over memorization.
• Language proficiency (at least English, but the more, the better).

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