Architect and scale the backbone of our AI Platform
Ensure high availability, low latency, and seamless integration of machine learning capabilities into production
Own the microservices that power AI inference
Build robust multi-tenant infrastructure
Support our Data & AI team with production-grade DevOps practices
Design, build, and maintain Go microservices that handle AI model inference
Architect scalable APIs (gRPC/REST) for production applications
Own the Kubernetes infrastructure (EKS)
Implement service-to-service communication using gRPC and message queues
Integrate with cloud AI services (AWS Bedrock, OpenAI, Anthropic)
Build multi-tenant capabilities including authentication, rate limiting, usage tracking, and tenant isolation
Partner with the Data & AI team to productionize machine learning models
Build comprehensive observability: structured logging, metrics, and alerting
Implement CI/CD pipelines and infrastructure-as-code for automated deployments
Ensure high availability through monitoring and incident response
Optimize resource utilization for GPU workloads and cost-efficient scaling strategies

3+ years of professional Go development experience
3+ years managing production Kubernetes clusters
Deep understanding of CAP theorem, eventual consistency, idempotency, circuit breakers, and fault-tolerant design
Hands-on experience with gRPC/Protocol Buffers and message queues (RabbitMQ, SQS, Kafka)
Strong experience with AWS services (EKS, S3, DynamoDB, Lambda) or equivalent cloud providers
Experience with Docker, CI/CD pipelines, infrastructure-as-code, and GitOps workflows
You communicate confidently in English (C1 level); German skills are a plus.

A remote working time model to keep your everyday life flexible
Exciting, challenging tasks in a dynamic, future-oriented environment
A culture of appreciation and a harmonious working atmosphere in a growing, international company
Attractive remuneration models, a permanent employment contract

AI Platform Engineer

Key skills