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Principal​/Backend Engineer — Distributed Systems

Job in Seattle, King County, Washington, 98105, USA
Listing for: Widenet Consulting
Full Time position
Listed on 2026-09-01
Job specializations:
  • Software Development
    Backend Developer, Cloud Engineer - Software, DevOps
Salary/Wage Range or Industry Benchmark: 170000 - 200000 USD Yearly USD 170000.00 200000.00 YEAR
Job Description & How to Apply Below
Position: PRINCIPAL / STAFF BACKEND ENGINEER — DISTRIBUTED SYSTEMS
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 back pressure Tail-latency management and performance tuning under load Reliability patterns, failure recovery, and incident response Large-scale relational and/or No

SQL 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  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
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