Engineering Manager - Client Delivery & Observability
Netflix - Los Gatos,California,United States of America
Posted Apr 28, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
- Not verified last checked Jun 13, 2026
- Salary
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- 401(k) match
- Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.
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Schedule
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Engineering Manager - Client Delivery & Observability Los Gatos,California,United States of America At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what's next. The Opportunity: The Client Delivery & Observability (CDO) team is a newly formed group that owns two connected domains at the heart of Netflix's client engineering: release delivery, the automation platform that safely ships client application updates to Netflix's over 300 million members across TV, TV Connected and mobile devices and real-time observability, the streaming analytics and canary analysis infrastructure that detects regressions before they reach members. Together, these systems ensure that every client release, server canary, and A/B test is both safely delivered and continuously monitored. The observability stack includes a multi-region streaming analytics platform built on Mantis, Kafka, and Druid that processes the full firehose of Netflix client telemetry This is a team that operates at the intersection of large-scale infrastructure engineering, release automation, and applied statistical methods. The system has caught regressions in production within seconds and on the delivery side, the release automation platform orchestrates deployments across all Netflix client surfaces, using A/B-test-based canaries to safely roll out new builds to millions of devices. The team continues to extend these capabilities to support Netflix's expanding
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