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Senior Forward Deployed Platform Engineer

Posted Updated
Discussion
  • 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 must
  • Knowing 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 teams
  • Familiarity 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 communications
  • Proficiency in Python, specifically with FastAPI and async task management
  • 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
  • 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.)

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