Top Tech Jobs & Startup Jobs in Vancouver

Lead engineering to build a unified platform for agent interactions with Workday Data Cloud, managing teams, and ensuring high-quality software delivery.

The role involves leading quality assurance by automating tests, enhancing platform scalability, mentoring SDETs, and collaborating with engineering teams on a SaaS contract management platform.

Lead a team of engineers developing the Agent Platform for AI agents. Responsibilities include roadmap execution, system design, best practices, and team development.

As a Senior Backend Software Engineer, you'll enhance the AI-driven contract management platform by collaborating with teams, optimizing code, and ensuring platform performance through API development and monitoring strategies.

The role involves designing, developing, and deploying scalable machine learning models and AI systems, focusing on end-to-end ownership of the ML lifecycle, collaborating cross-functionally, advocating for technical excellence, and mentoring junior engineers while championing Responsible AI practices.

The role involves managing a software engineering team, collaborating with product and design teams, and driving AI initiatives for contract management solutions.

As a Principal Machine Learning Engineer, you'll design and implement core ML systems for AI agents, collaborating with cross-functional teams and overseeing the full lifecycle of products from data strategy to deployment.

Lead overall success for an assigned portfolio of Workday subscribers: build executive relationships, orchestrate cross-functional resources, drive adoption and subscription retention/growth, and deliver exceptional customer experiences while supporting deployments and ongoing production.

Lead a team to design, build, and deploy scalable AI agents for HR and Finance. Define tooling and framework choices, integrate LLMs and orchestration, implement RAG and vector search, ensure compliance, monitoring, and continuous learning, and collaborate across product, engineering, and vendors to deliver enterprise-grade AI automation.

Lead technical direction and implementation of a large-scale AI model serving platform. Design, build, and operate distributed systems (Ray/Ray Serve), ensure scalability, reliability, monitoring (Prometheus), CI pipeline robustness, and evolve the production model registry while collaborating with ML engineers and stakeholders.