Staff Software Engineer - Core Ingest
Sumo Logic - United States, Remote
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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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Assessment
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- Deadline
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Where they hire
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About this role
Staff Software Engineer - Core Ingest United States, Remote Staff Software Engineer - Core Ingest The proliferation of machine log data has the potential to give organizations unprecedented real-time visibility into their infrastructure and operations. With this opportunity comes tremendous technical challenges around ingesting, managing, and understanding high-volume streams of heterogeneous data. As a Staff Software Engineer - Core Ingest, you will actively contribute and lead engineers in the design and development of new distributed data processing capabilities. You will be instrumental in helping us solve complex, low-latency, distributed systems challenges to handle our ever-increasing scale. Our system is a highly distributed, fault-tolerant, multi-tenant platform that includes bleeding-edge components related to storage, messaging, search, and analytics. This system ingests and analyzes petabytes of data a day, while making exabytes of data available for search and forensic analysis. You are a strong software engineer who is passionate about large-scale systems. You care about producing clean, elegant, maintainable, robust, well-tested code; you do this as a member of a team, helping the group come up with a better solution than you would as individuals. Ideally, you have experience with performance, scalability, and reliability issues of 24x7 commercial services. Responsibilities: - Designing and implementing extremely high-volume, fault-tolerant, scalable backend systems that process and manage petabytes of customer data. - Work to improve algorithms built to schedule load on clusters of thousands of machines elastically at runtime. - Experience in multi-threaded programming and distributed systems - Improve systems to provide performance guarantees to customers
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