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Seattle , Washington Posted: 2026-08-04 Job Type: Direct Hire APPLY Principal / Staff Backend Engineer — Distributed Systems Full-Time | Remote-Friendly | Equity Included We are partnering with a venture-backed technology company to place two senior backend engineers into newly opened Staff and Principal-level roles. The platform is already in production and operating at scale — this is not a greenfield build. These engineers will step into real ownership of complex, high-volume systems from day one. We are recruiting for two distinct technical backgrounds simultaneously and expect to place one engineer from each track. If your experience fits either profile below, you are a complete candidate — you do not need to cover both. What You’ll Own These roles sit at the intersection of backend engineering and production operations. The work involves designing and operating services that process very high query and data volumes across a shared, multi-tenant environment. The core technical challenge is building systems that stay fast, fair, and predictable regardless of how much variance exists across customer workloads — and doing so without a dedicated SRE or platform team to hand things off to. Engineers in these roles own their systems fully: architecture decisions, implementation, deployment, observability, and on-call. If you prefer writing specs over writing code, or handing finished designs to an ops team, this is not the right fit. If you want deep technical ownership and the ability to drive how a production platform evolves, it is. You’ll Be Successful Here If You Can • Design and operate services that handle extreme variance in workload size without one customer impacting another • Build systems that fail gracefully, recover predictably, and do not require manual intervention to stay healthy • Identify and eliminate bottlenecks across complex, multi-stage data pipelines • Establish engineering patterns your teammates can actually use — not just document them • Own infrastructure, code, and deployment configuration as a single responsibility rather than separate concerns Track 1 — Distributed Services & Infrastructure You have spent your career building and running high-volume, low-latency backend services. You understand what happens to a shared system when traffic patterns shift, tenants misbehave, or upstream dependencies slow down — and you know how to engineer around it. Core areas of depth likely include: • Distributed systems design and production operation • Multitenancy, workload isolation, and resource fairness • Queuing, scheduling, admission control, and backpressure • Tail-latency management and performance tuning under load • Reliability patterns, failure recovery, and incident response • Large-scale relational and/or NoSQL data stores • Infrastructure as code and deployment automation Strong candidates for this track have worked on infrastructure or service teams at cloud-scale companies, high-volume SaaS platforms, or other environments where the system itself is the product. Track 2 — Unstructured Data & Document Pipelines You have built the systems behind large collections of complex, unstructured content — ingestion, processing, indexing, storage, and retrieval at volume. You understand the engineering challenges that arise when documents vary in size, structure, and relationship to one another, and you have built pipelines robust enough to handle that variance reliably. Core areas of depth likely include: • High-volume document ingestion and transformation pipelines • Search, indexing, and retrieval systems at scale • Data modeling for heterogeneous, relationship-rich document collections • SQL, Cosmos DB, or comparable distributed data stores • Large-scale asynchronous processing architectures • Deduplication, document threading, metadata extraction, and content enrichment Strong candidates for this track have built the data layer at search companies, content platforms, data infrastructure businesses, or SaaS products where managing large volumes of complex documents is core to the product. What We’re Looking For Across Both Tracks • 7+ years of backend engineering experience at Staff or Principal level — or equivalent demonstrated scope • A proven track record building, shipping, and operating production systems under real load • Experience with large-scale, latency-sensitive services • A preference for staying technical and hands-on rather than transitioning into management or advisory work • The ability to own a problem from whiteboard to production without handoffs Compensation Base salary: $170,000 – $200,000 depending on experience and background. Equity is included and is a meaningful part of the total package. Comprehensive benefits. This is a direct-hire, full-time position. The compensation range above reflects base salary only. Equity grant details provided during the interview process. Final offer determined based on experience, depth, and qualifications Back to Job Listings 🢒 WideNet Consulting widenet-consulting.com widenet-consulting.com Apply for this job Share Job on LinkedIn Share Job on Twitter

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Seattle , Washington
Posted: 2026-08-04
Job Type: Direct Hire
Principal / Staff Backend Engineer — Distributed Systems
Full-Time | Remote-Friendly | Equity Included
What You’ll Own
You’ll Be Successful Here If You Can
Design and operate services that handle extreme variance in workload size without one customer impacting another
Build systems that fail gracefully, recover predictably, and do not require manual intervention to stay healthy
Identify and eliminate bottlenecks across complex, multi-stage data pipelines
Establish engineering patterns your teammates can actually use — not just document them
Own infrastructure, code, and deployment configuration as a single responsibility rather than separate concerns
Track 1 — Distributed Services & Infrastructure
Distributed systems design and production operation
Multitenancy, workload isolation, and resource fairness
Queuing, scheduling, admission control, and backpressure
Tail-latency management and performance tuning under load
Reliability patterns, failure recovery, and incident response
Large-scale relational and/or NoSQL data stores
Infrastructure as code and deployment automation
Strong candidates for this track have worked on infrastructure or service teams at cloud-scale companies, high-volume SaaS platforms, or other environments where the system itself is the product.
Track 2 — Unstructured Data & Document Pipelines
High-volume document ingestion and transformation pipelines
Search, indexing, and retrieval systems at scale

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sql

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