About the Role
This role involves developing and maintaining backend systems that support data processing and AI workloads, with a focus on scalability, reliability, and integration across services.
Responsibilities
- Design and implement scalable backend services for data and machine learning workflows
- Build robust APIs to connect internal systems and external tools
- Optimize data pipelines for efficiency and reliability
- Collaborate with data scientists and ML engineers to support model deployment
- Ensure backend systems handle high throughput and low latency
- Maintain and improve system observability and monitoring
- Write clean, maintainable, and well-tested code
- Troubleshoot and resolve production issues promptly
- Evaluate and integrate new technologies into the stack
- Participate in architectural discussions and system design
- Support secure handling of sensitive data
- Improve developer tooling and internal workflows
- Document system design and operational procedures
- Contribute to capacity planning and scaling strategies
- Work closely with product teams to understand infrastructure needs
- Help define best practices for backend development
- Ensure compliance with data governance policies
- Monitor system performance and respond to anomalies
- Refactor legacy components for better maintainability
- Collaborate on disaster recovery and backup strategies
Nice to Have
- Experience with large-scale data processing systems
- Contributions to open-source infrastructure projects
- Familiarity with AI/ML workflows and tooling
- Experience with infrastructure as code tools like Terraform
- Knowledge of service mesh and API gateway patterns
- Background in observability and metrics collection
- Prior work in early-stage or high-growth startups
- Understanding of data privacy and security standards
Compensation
Competitive salary with equity and benefits
Work Arrangement
Hybrid with office presence in Berlin
Team
Small, cross-functional engineering team focused on infrastructure and data systems
Tech Stack
- Go for core services
- Kubernetes for orchestration
- PostgreSQL and Redis for data storage
- AWS for cloud infrastructure
- Prometheus and Grafana for monitoring
- GitLab CI for pipelines
- gRPC and REST for APIs
Impact
- Your work will directly shape the foundation of a data and AI platform used by internal teams
- You’ll enable faster iteration on machine learning models through reliable infrastructure
- Systems you build will support real-time data processing at scale
- You’ll influence engineering standards across the backend ecosystem
Available for qualified candidates
