Build the Market Leader in Satellite Analytics with us at LiveEO
You will work on applications that use deep learning and satellite data and other data sources to help companies and governments fight deforestation, monitor critical infrastructure, and respond faster and more precisely to natural disasters. Our aim is to empower any user in the world to harness the power of earth observation satellites to simplify and improve their daily work.
You will join the team that turns analytics outputs into data products and makes them available across the platform and to customers. We already have deep geospatial and data engineering expertise in the team; what we need is a strong generalist software engineer who makes our core services and pipelines more reliable, observable and scalable. Concrete topics you would work on are, for example, the performance and scalability of backend services serving large volumes of geospatial data, the health and observability of our end-to-end processing pipeline, and the stability of the interfaces between the services that make it up.
We are a team of five engineers and three geospatial analysts today, embedded in a cross-functional group of product managers, UX/UI designers, data, devops, ML, and geospatial engineering experts. You will not be the only person responsible for any system you touch, but you will play a crucial role in how we evolve our services and components.
Your challenge
- Own the maintenance, performance and scalability of core backend services, evolving their data models, APIs and storage as data volumes and consumers grow.
- Maintain a clear, shared view of the health of the end-to-end product pipeline so that regressions and failures are detected early rather than discovered late or through manual coordination.
- Build and uphold the practices that make this possible: monitoring, alerting, automated quality checks and testing across services.
- Help keep the interfaces between services stable: spot schema drift, contract failures and version incompatibilities early, feed concrete failure cases back to the owning engineers and help establish durable contracts.
- Contribute to safer release practices such as backwards compatibility, feature flags and staged rollouts.
- Maintain and improve our workflow orchestration and the automation around it, reducing manual steps and operational toil.
- Turn observed system behaviour into concrete improvement work and bring it into team planning.
- Mentor engineers through code review and pairing; raise the bar on scoping, testing and release stability.
Stack
- Backend: Python
- Orchestration: Prefect, Anyscale, K8s
- Database: PostgreSQL / PostGIS (including geospatial workloads)
- Infrastructure & CI/CD: Gitlab, AWS