Location: LATAM (remote)
The role
We're hiring a hands-on Senior Site Reliability Engineer to keep FileScience reliable for customers. Some of the hardest failures are quiet ones: a backup stops making progress, finishes with files missing, or reports success when it shouldn't. You'll work with our engineering team to catch these problems, improve monitoring and incident response, and fix reliability issues in production code and infrastructure.
What you will do
01 Define how we measure reliability. Set service-level indicators and objectives (SLIs/SLOs) for product availability and backup jobs. Show what we can and cannot yet measure, and use the results to decide what to improve first.
02 Make failures easier to find. Add logs, metrics and traces that identify the affected customer and job. Build useful alerts, reduce noise, and regularly check that monitoring works and alerts reach the right person.
03 Lead incident response. Maintain incident tools, escalation paths and runbooks. Diagnose problems, keep people informed, confirm service has recovered, and follow through on fixes that prevent repeat incidents.
04 Check that backups actually work. Build checks for whether each customer's backups run when expected, capture the expected data and can be restored. Work with product engineers to compare source and backup data and test recovery.
05 Automate recurring operational work and ship reliability fixes. Work with product engineers on safer deployments, growing workloads, queue backlogs and third-party API failures. Test changes before rollout, keep a rollback path where possible and verify the result.
Core experience
. Hands-on experience keeping production systems reliable after launch, including responding to incidents and improving the systems over time.
. Strong AWS troubleshooting skills across services, networks, containers, storage, queues and databases. You can investigate problems that involve both application code and infrastructure.
. Experience building and maintaining observability, SLOs, useful alerts, runbooks and recovery tests in production.
. Ability to read, debug and change production Python code and build dependable automation. Practical understanding of partial failures, retries, idempotency, concurrency and backpressure.
. Experience with infrastructure as code, CI/CD and safe production changes, including testing, rollback and access controls.
. Clear written and spoken English, good organization and independent problem-solving. You can turn incomplete requirements into a practical plan, prioritize your work and communicate progress, risks and decisions.
Nice to have
. Experience with backup, synchronization or data-integrity systems, or data pipelines that run for long periods across many customers.
. OpenTelemetry, Grafana, Sentry or incident-management platforms, or comparable tools.
Our stack
Python and AWS: ECS, Lambda, Step Functions, S3, SQS, DynamoDB, Aurora PostgreSQL and CloudWatch.
How we work
We work in a fast-paced environment where priorities change and requirements may be incomplete. You will be expected to work autonomously: investigate problems, identify next steps, make sound decisions and drive work forward without waiting for detailed instructions.
Keep the engineering team informed and involve others when their input is needed.
We value practical production experience, sound judgment and seeing work through.