Principal Engineer - Zynque
$175–$210,000 year
HybridToronto, Ontario, Canada
Job Summary
Own technical direction and architecture evolution of a live, revenue-generating platform, scaling throughput and reliability while customers onboard. Harden the system with tenant isolation, rate limiting, and security measures to ensure data integrity. Establish observability, SLOs, and incident practices as the customer base grows, leading performance and capacity work ahead of demand. Raise engineering standards through design reviews and mentorship while partnering with Product to balance platform investment against feature delivery. Identify and retire scaling risks and technical debt before they compound. Drive zero-downtime changes to running systems under real load, transforming a young production platform into an enterprise-grade solution trusted by global commerce operations.
Required Qualifications
- 10+ years building and operating cloud-native backend or platform systems
- Owned the scaling of a production SaaS or data platform through rapid customer growth: hardening, re-architecture under load, and maturing an early product to enterprise grade
- Deep hands-on experience with high-throughput distributed systems: event streaming or message queues, async processing, idempotency, retries, backpressure
- Strong performance engineering: profiling, load testing, horizontal scaling, capacity planning
- Production reliability ownership: observability, SLOs, incident management, fault-tolerant design
- Multi-tenant SaaS experience, including tenant isolation and noisy-neighbor problems
- Proficiency in Python and JavaScript/TypeScript (Next.js)
- Hands-on daily coder with founder-level ownership; comfortable in low-process, high-ambiguity environments
Desired Qualifications
- Built or scaled an integration platform, ETL/data pipeline product, or API platform (connectors, transformation pipelines, webhooks)
- Kafka or similar streaming infrastructure at scale
- Supply chain or logistics systems exposure (WMS, OMS, TMS, EDI integrations)
- AI-assisted engineering workflows; AI is deeply embedded in how we build
- Experience shipping AI/LLM-driven capabilities in production (rag, generation pipeline, agentic workflows)
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