Top Tech Jobs & Startup Jobs in Vancouver

Own and improve incentive compensation systems and commission operations. Assess workflows, replace manual processes with scalable automation, configure and optimize Xactly, integrate CRM, HRIS, data warehouse, and compensation platforms, and use SQL to reconcile data and validate outputs. Build AI-enabled workflows, establish documentation and controls, and partner cross-functionally with Finance, People Operations, Revenue Operations, IT, and Data teams.

Lead marketing analytics as the architect of the data-driven growth engine: build BigQuery data schemas, predictive models (attribution, MMM, LTV), agentic AI monitoring, automated orchestration, executive BI, and target-setting frameworks to optimize demand generation and funnel quality across GTM.

Support Grafana's AI organization by defining KPIs, designing experiments, guiding instrumentation, building dbt models, creating dashboards, and translating analytics into product recommendations to improve AI-powered features and workflows.

Lead architecture and delivery of large, distributed telemetry database systems for Grafana Cloud. Own reliability, performance, cost, SLOs/SLIs, incident response, observability, automation, and cross-team alignment while mentoring engineers and driving technical strategy.

The role involves leading AI-driven nurture programs, executing multi-channel campaigns, and analyzing data to enhance demand generation for Grafana Labs.

Design, prototype, and ship production AI/ML features that analyze observability data to detect, triage, and resolve incidents. Rapidly iterate on LLM- and agent-powered workflows, collaborate cross-functionally, integrate AI with internal tools and alerting systems, and ensure solutions are scalable, maintainable, and aligned with user workflows.

As a Staff Backend Engineer at Grafana Labs, you'll lead technical initiatives for Tempo's development, ensuring operational excellence and integrating with other products while mentoring engineers and contributing to open source.

Design, build, and operate production multi-agent AI systems and automation for Marketing Operations. Integrate LLMs with business systems (BigQuery, CRMs, Slack), implement RAG pipelines, observability, governance, and scalable serverless/containerized services. Partner with GTM teams to deliver measurable automation and self-service tooling.

Own and run customer lifecycle demand-generation programs to drive expansion, cross-sell, and adoption across email, in-app, web, paid, events, and outbound. Build AI-driven, agentic workflows to automate execution, align programs with sales motions, instrument pipeline impact, and partner with sales and customer teams to optimize coverage and results.

Design, build, and operate core backend services for an AI-native context management system: ingestion, indexing, retrieval APIs, multi-tenant SaaS features, and agent-facing integrations. Define architecture, ensure observability, iterate from prototype to production, and collaborate across product and infrastructure while owning service reliability and technical direction.