Automation, Automation Engineering, Bridge Building, Bug Tracking Software, Cadence, Code Reviews, Communication Systems, Configuration Management, Continuous Improvement, Data Management, Documentation, Environmental Issues, Equipment Maintenance/Repair, Establish Priorities, Government, Hospital, Metrics, Network Connectivity, Operational Improvement, Process Improvement, Protocol Stack, Quality Assurance Methodology, Radio Frequency, Regression Testing, Regulations, Reporting Dashboards, Requirements Management, Resource Management, Risk, Signal Processing, Software Architecture, Software Engineering, Software Testing, Software Validation, System Architecture, System Integration (SI), System Test, Systems Engineering, Test Automation, Test Design, Test Plan/Schedule, Test Requirements, Testability, Testing, Traceability, United States Citizen, Wheel/Front-End Loader
Amazon Leo is Amazon"s low Earth orbit satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks. From individual households to schools, hospitals, businesses, and government agencies, Amazon Leo will serve people and organizations operating in locations without reliable connectivity.
Behind every satellite in our constellation is a payload - the communication system that makes connectivity possible. Before a single satellite reaches orbit, its payload software must be validated through automated nightly regression testing that catches defects early and accelerates release cadence.
We are hiring an Integrated Systems Engineer to own the requirements, operations, and continuous improvement of nightly regression test runs for payload software. You will bridge payload software teams, test automation engineers, and operations to define what we test, how we measure success, and how we drive nightly run reliability from its current state toward fully-automated execution.
This role requires someone who wants to understand how payload software works at a system level-signal routing, beam management, protocol handling, fault recovery-and translate that understanding into clear test requirements and operational improvements.
You will not write test automation code full-time. You will define what the automation must validate, ensure nightly runs execute reliably, triage systemic failures, and drive process improvements that make the regression pipeline more effective every week.
What Makes This Role Different
You sit at the center of payload software testing operations. You understand the payload system deeply enough to define what must be tested, you understand the automation infrastructure well enough to diagnose why nightly runs fail, and you own the operational cadence that turns raw test results into actionable engineering decisions every morning. You are the person who makes nightly regression runs trustworthy.
Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
Key job responsibilities
- Develop working knowledge of payload software architecture-signal processing chains, protocol stacks, resource management, and fault handling-to define comprehensive test requirements.
- Collaborate with payload software engineers, systems engineers, and RF engineers to gather and document test requirements for new features, bug fixes, and configuration changes.
- Own operational health of nightly regression runs: monitor execution, triage failures, distinguish test infrastructure issues from real payload software defects, and drive resolution.
- Define and track metrics for nightly run effectiveness-pass rates, flakiness, coverage gaps, cycle time-and present improvement plans to stakeholders.
- Identify patterns in nightly run failures and work with automation engineers to implement fixes that prevent recurrence.
- Collaborate with internal and external customers to define and implement system architectures for integrated test venues.
- Develop and maintain test plans, test matrices, and traceability documentation linking requirements to automated test coverage.
- Coordinate with test automation engineers to prioritize new test development based on risk, coverage gaps, and payload software roadmap.
- Design complex test sequences that coordinate and synchronize equipment and services across multiple layers to verify function and performance of satellite hardware and software.
- Drive process improvements for test environment configuration, data management, and results reporting.
- Participate in design reviews and payload software planning to provide early input on testability and regression impact.
A day in the life
You arrive and check the nightly run dashboard. 847 of 860 tests passed. Of the 13 failures, you quickly categorize: 4 are a known test environment issue (hardware-in-the-loop bench lost network connectivity at 2 AM-you escalate to infra), 6 are caused by a payload software change merged yesterday (you file a defect with clear reproduction steps and link to the failing test logs), and 3 are flaky tests you have been tracking (you add them to the backlog for the automation team with a proposed fix approach). By 10 AM, you join a requirements review for an upcoming beam handoff feature-you ask questions about edge cases and failure modes, then draft test requirements that will feed the automation team"s sprint. After lunch, you update the weekly metrics dashboard showing nightly run reliability trending from 94% to 97% over the past month, and present your proposal to add coverage for a protocol state machine that currently has no regression tests.
About the team
The STAR (System Test Automation and Regression) team for payload test automation builds the regression-testing backbone for payload software. We own the frameworks, pipelines, and infrastructure that validate every payload software release before it reaches a satellite. We operate at the boundary between software engineering and satellite systems-our engineers understand both domains and bridge them through automation.
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Amazon.com Inc
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