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LiveEO builds applications that combine deep learning, satellite data, and other data sources to help companies and governments combat deforestation, monitor critical infrastructure, and respond to natural disasters. You will join the backend team responsible for turning analytics outputs into reliable, scalable data products available across the platform and to customers.
As a Senior Backend Engineer, you will own the maintenance, performance, and scalability of core backend services, evolving their data models, APIs, and storage as data volumes and customer base grow. You will maintain clear visibility into the health of the end-to-end product pipeline, detecting regressions and failures early through monitoring, alerting, automated quality checks, and comprehensive testing across services. You will help establish and uphold practices that ensure system reliability, including backwards compatibility, feature flags, and staged rollouts.
Key responsibilities include: maintaining and improving workflow orchestration and automation to reduce manual operational work; spotting schema drift, contract failures, and version incompatibilities between services; contributing concrete failure cases and improvement recommendations to team planning; and mentoring engineers through code review and pairing to raise standards around scoping, testing, and release stability.
The team currently consists of five engineers and three geospatial analysts, embedded within a cross-functional group including product managers, UX/UI designers, data engineers, DevOps, ML specialists, and geospatial experts. You will play a crucial role in evolving services and components, though you will not be solely responsible for any single system.
Tech stack: Python backend, Prefect and Anyscale for orchestration, Kubernetes for infrastructure, PostgreSQL/PostGIS for databases, GitLab and AWS for CI/CD and infrastructure.
Requirements:
Must have:
- At least 5 years of experience building and operating production backend services or data pipelines in Python
- Solid track record maintaining and scaling production services: performance optimization, observability, testing, incident handling
- Strong relational database skills; comfortable with API design and service-to-service contracts
- Hands-on experience deploying and operating services on Kubernetes, including troubleshooting and incident response
- Regular use of AI-assisted coding in day-to-day work (not just trial experience)
Nice to have:
- Geospatial data experience (PostGIS or similar)
- Raster processing or satellite imagery background
- Spec-driven or test-driven development experience
- Experience with workflow orchestrators (Prefect, Airflow, or similar)
- AWS workload experience
- Cross-team collaboration on shared interfaces or contracts
Note: You do not need to match every requirement perfectly; if you believe you would be a good fit but are missing items, you are encouraged to apply and explain what you would bring instead.
