102K–118K USD / year
Platform Engineer (Backend Infrastructure)
DevOpsRemote — Poland, Europe
Published on 2026-11-13
These details were extracted automatically from the original listing. They may not be complete or fully up to date — it's worth checking the original job post.
About this role
Own and scale the cloud platform that processes hundreds of millions of retail images daily. The role combines infrastructure operations with hands-on Python backend work, focusing on reliability, throughput, latency, and cost efficiency.
About the company
Focal Systems uses computer vision and deep learning to automate shelf monitoring for brick-and-mortar retailers, reducing manual scanning and improving in-store operations.
Stack
GCPKubernetesKafkaPythonFastAPIMySQLMongoDBRedis
What you'll do
- Operate and manage production infrastructure, including Kubernetes, streaming, databases, and object storage.
- Reduce infrastructure costs and latency, measuring and reporting outcomes.
- Debug and change Python backend services to address platform issues.
- Diagnose and resolve throughput bottlenecks across messaging, databases, and autoscaling.
- Improve metrics, alerts, dashboards, incident response, and capacity planning.
- Build tools for faster access to data across regions and storage systems.
- Maintain infrastructure as code and the production deployment path.
What we're looking for
- Professional Python development experience, including regular backend contributions.
- 5+ years building and operating production backend systems on a cloud platform.
- Production experience operating a stateful system under load, such as Kafka, MySQL/PostgreSQL, or MongoDB.
- Production Kubernetes experience, including scheduling, autoscaling, GPU node pools, and pod debugging.
- Experience debugging production incidents across application and infrastructure layers.
- Experience with observability tools such as Prometheus, Grafana, Grafana Mimir, or Sentry.
- Experience with Terraform or another infrastructure-as-code tool.
- Advanced English and comfort with global coordination and shared on-call.
Nice to have
- MySQL query tuning and Kafka internals.
- Production GPU workloads or ML inference serving, and measured cloud cost optimization.
- Go, Snowflake, Airflow, CircleCI, Helm, or blue/green and canary releases.
Benefits
- Stock options
- Paid time off
- Team retreats
- Education grants