Top Tech Jobs & Startup Jobs in Vancouver

Build backend systems powering AI agents: data pipelines, integrations, and agent infrastructure. Contribute to features like Atlas, Activity Stream, dynamic knowledge, and agent memory. Work closely with senior engineers, ship production-quality code, and own smaller projects end-to-end as you ramp up.

Build backend systems for AI agents, including data pipelines, integrations, agent infrastructure, logging/visualization, dynamic knowledge, and memory; ship features while paired with senior engineers and own smaller projects end-to-end.

Own end-to-end fullstack features for an AI voice platform: design schemas and APIs, build frontend interfaces and analytics dashboards, implement conversation storage and onboarding pipelines, and iterate with product and design to ship polished customer-facing functionality.

Build and maintain the platform powering Giga's AI agents: design controlled deployments, observability, data pipelines/storage, and developer tooling. Own critical infrastructure end-to-end to improve reliability, developer velocity, and production debugging.

Build and maintain backend infrastructure powering real-time AI agents. Work across data pipelines, analytics, and real-time systems. Own end-to-end solutions, scale services (e.g., ClickHouse migration), improve hallucination detection, and stabilize browser-agent features while shipping reliable, high-quality code.

Build and maintain frontend infrastructure: design systems, developer tooling, code quality guardrails, and architecture patterns to improve frontend developer experience and scalability.

Lead and execute backend technical strategy and architecture for scalable AI agent infrastructure. Own and ship high-stakes projects, mentor engineers, set engineering quality standards, and identify systemic gaps to ensure reliability and performance.

Lead and grow the Toronto engineering site, shape platform architecture, own and ship critical systems, hire and mentor engineers, set engineering quality standards, and solve high-stakes scalability and reliability problems for enterprise voice AI products.