Senior Forward Deployed Platform Engineer

• This is how you will make an impact as a Senior Forward Deployed Platform Engineer:
• Our AI portfolio needs to run reliably and perform well. Thus it has to be properly monitored
• Capacity needs planning, support scaling initiatives, and ensure our systems remain stable as the company grows
• SageMaker models need to be continuously delivered, following AWS’ best practices
• AI engineers need assistance with productionalizing AI workloads end-to-end, from code to container build, and rollouts using optimal deployment strategies
• We run a modern cloud-native stack to build, ship, and operate AI workloads reliably in a regulated healthcare environment
• Cloud: AWS (The European Sovereign Cloud partition)
• Runtime: Kubernetes and Postgres
• Inference: Bedrock, SageMaker, ClearML
• Observability: Datadog, LangFuse, OTEL
• CI/CD: GitHub Enterprise Cloud with Actions
• Plus various auxiliary tools for security, compliance and operations: DockerHub, Google as IdP, SonarCloud, VPNs, QuickSight, CDN, Snowflake, ETLs, etc

Benefits

• Flexibility in how you work: Work is not measured by hours or location. Work remotely, come to the office, or spend time working from abroad.
• Staying connected: We stay in touch through clear communication and the right tools. Work is transparent, and teams stay aligned without unnecessary overhead.
• Trust and space to focus: We trust people to manage their work and take breaks when needed. What matters is staying focused and moving things forward.
• Work from abroad: Spend time working abroad, up to 182 days per year. We support flexible setups beyond your usual location.
• Office space in Berlin: A central place in Berlin Mitte where people come together to meet and collaborate. Join whenever you feel like it.
• Learning & Development: Grow through regular feedback, clear development paths, and a dedicated learning budget.
• Your birthday, full off: Take an extra day off to celebrate yourself. No Slack, no calls, no work.
• Tools, hardware & AI: We equip you with a MacBook Pro, modern collaboration tools, and AI that is part of how you work every day.
• Monthly Edenred card: Enjoy a €50 monthly budget on your Edenred card, flexible to use online or in-store.
• Choose your own setup: Pick the tech and equipment you prefer. We support you with a dedicated budget.
• Time together: Regular opportunities to connect and spend time together, from team meetups to company-wide events.
A strong team around you: Work with people who take ownership, support each other, and enjoy working together.

Experience deploying SageMaker models, setting up custom inference containers (HuggingFace and/or OSS model) and endpoints (provisioning, autoscaling, and blue/green rollouts)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 mustKnowing how to set up ML/LLM GPU inference on EKS (GPU-backed instances, Nvidia driver/plugin)Experience with Kubernetes (EKS) in production (kustomize, HPA and KEDA based autoscaling)Experience with AWS (CloudFormation, IAM, ECR, SageMaker, Bedrock, S3, SQS, DynamoDB, RDS, KMS)Ability to own technical decisions and collaborate directly with other teamsFamiliarity with observability & LLMOps best practices and solutions (Datadog, Langfuse, LLM/GenAI tracing, OTel, CloudWatch)Preference for writing over talking, resulting in clear, concise, yet complete documentation and asynchronous communicationsProficiency in Python, specifically with FastAPI and async task managementTroubleshooting, 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 neededHealthcare or regulated-domain experience (e.g. ISO 27001, C5)Self-hosting/home labNvidia Triton/vLLM or similarMLflow, Kubeflow, ClearML, DVC, Vertex AI Slack and GitHub automations (bots, workflows, apps, etc.)