acquird - Staff Platform Engineer
Requirements
• You've architected backend systems that other teams build on, owning the service boundaries, data models, and API contracts in production (Node.js and TypeScript; strong engineers from similar stacks transfer well) • You've led complex, multi-engineer backend projects from design through production, and been the technical decision-maker when trade-offs were contested • AI-native development habits: you direct AI coding tools (Claude Code, Cursor, Copilot, or similar) through much of your output, and rigorously review and own what ships • You've designed asynchronous, event-driven systems (queues, background jobs, messaging) that run under real production load, not just consumed them • You've owned hard third-party integrations end to end, including auth, rate limits, retries, and failure modes (ad-platform APIs like Meta's are a plus) • You've simplified data architecture at scale: schema design, ETL pipelines, and storage choices (PostgreSQL, MongoDB, or other document stores) that held up as data volume grew • 6+ years building and maintaining large-scale software applications, with recent years operating at a Staff or Lead IC level: setting technical direction, not just executing it • A track record of taking products from 0 to 1, ideally at Series A to C startups • You raise an engineering team's bar: design reviews, mentoring, and standards other engineers adopt • Comfort with a fast pace: short project cycles, evolving requirements, high ownership • Exceptional written and verbal communication, including translating technical issues into business impact • Experience building or integrating LLM-powered product features or agent systems • Able to work with significant overlap to Eastern Time • Founder or founding-engineer experience • Experience with Azure or another public cloud platform • Experience in adtech, martech, or marketing/creative analytics
Benefits
• CA$200K – CA$250K • Offers Equity • Upload your resume here to autofill key application fields. • Drop your resume here! • Parsing your resume. Autofilling key fields... • or drag and drop here • Intermediate (shipped production features in Node/TS as one of my stacks) • Very Strong (Node/TS has been my primary backend stack for years; I've built and owned production services with it) • Expert (platform-level Node/TS depth: performance profiling, typing strategy, patterns and tooling other engineers adopt) • Intermediate (designed features within an architecture someone else owned) • Very Strong (owned the architecture of a major service or domain: boundaries, data models, API contracts) • Expert (owned APIs and services that other teams built on, and made the call on contested design decisions) • Intermediate (worked with existing pipelines and data stores) • Very Strong (designed the schemas, queues, and pipelines that handled real production volume) • Expert (owned data architecture at scale: simplified it, kept it reliable as volume multiplied, and set the patterns others follow) • Intermediate (built or maintained integrations within an established pattern) • Very Strong (owned production integrations end to end, including the failure modes) • Expert (set the integration architecture others build on, across many external APIs) • Intermediate (regular AI assistance on parts of my work) • Very Strong (AI tools produce a large share of my output, under my direction and review) • Expert (my workflow is built around AI agents: I direct them through most of my output, own the quality bar, and keep upgrading how I use them) • Intermediate (limited startup experience, or I shipped mostly within direction someone else set) • Very Strong (solid startup experience; I led complex features through ambiguity to launch, creating the clarity myself) • Expert (repeatedly launched complex features or platforms at scaling startups, owning the outcome end to end under real pressure)
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