Top AI Jobs in Vancouver

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, design and run experiments (A/B tests and AI evaluations), implement AI infrastructure for reliable LLM inference, and iterate quickly to scale production-ready LLM-powered products.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

As an AI Transformation Owner at GitLab, you will shape AI strategies, improve workflows, and drive adoption of AI solutions in your organization, working closely with an AI Engineer.

Lead technical vision and architecture for AI-powered GTM systems, defining reference architectures, patterns, and governance for low-code and custom agentic solutions. Architect and prototype LLM orchestration, multi-system integrations, RAG pipelines, and event-driven data flows across Salesforce, NetSuite, Marketo, and cloud infrastructure while partnering with GTM leaders to deliver production-grade, auditable, and scalable automation.

Lead product vision and strategy for an end-to-end AI-powered software factory. Integrate planning, coding, review, and verification across GitLab Duo Agent Platform and product areas. Collaborate with engineering, design, and GTM teams, identify gaps and dependencies, present recommendations to executives, and drive execution to deliver cohesive developer workflows.

Build and maintain backend features for Agent Observability across the GitLab monolith and AI gateway. Design and implement GraphQL/REST APIs, improve automated tests (RSpec), collaborate cross-functionally, troubleshoot production issues on Tier 2 on-call, and help shape responsible AI integration and platform architecture.

Manage a cross-functional engineering team building GitLab Duo Chat's AI-powered features. Define requirements with product and UX, contribute to architecture for scalable agentic AI, drive delivery and roadmap execution, improve testing, observability, performance, and coach engineers to foster an inclusive, high-performing team.

As a Staff Machine Learning Engineer, you'll lead AI initiatives using large-scale data, optimize ML models for edge devices, and collaborate with cross-functional teams.

Lead architecture and technical strategy for AI-driven product quality systems using LLMs and agents. Build scalable evaluation frameworks, detect regressions, generate insights, and drive cross-functional adoption while mentoring engineers and defining standards for trustworthy AI.

Lead end-to-end design for AI-powered developer tools at GitLab. Create flows, wireframes, prototypes, and high-fidelity interfaces for AI agents, chat, and code-assist features. Define success metrics, iterate with PMs and engineers, establish AI-specific design patterns in the design system, mentor other designers, and contribute to product strategy and research-informed decisions.

Lead multi-year vision, strategy, and roadmap for Webflow's agent surfaces and AI platform. Align cross-functional teams, set quality standards and guardrails for non-deterministic agent experiences, serve both developers and creators, prototype and ship product improvements (including contributing code), and mentor PMs while measuring and iterating on outcomes.

Lead product strategy and roadmap for Webflow's agentic AI surfaces (AI Assistant, MCP, Agent Instructions, and underlying AI platform). Define quality metrics, guardrails, and evaluations for non-deterministic agent experiences. Balance developer-focused APIs/platforms with approachable creator UX, work closely with engineering/design/data, prototype and ship features (including contributing code), and adapt strategy as AI models and protocols evolve.

Lead development and implementation of AI legal and compliance frameworks. Conduct cross-functional AI reviews, maintain governance docs (model cards, impact assessments), partner with engineering on transparency and fairness requirements, build incident response and monitoring processes, and scale AI legal review workflows.

Build, deploy, and maintain AI-powered agents, APIs, and applications for People operations on Snowflake. Integrate Workday/Notion, ensure security and data governance, design multi-model LLM reliability, and own production lifecycle including CI/CD, monitoring, and incident response while working with non-technical stakeholders.

Ownership of backend features for Agentic Tools: design and implement GraphQL/REST APIs, build secure scalable Ruby on Rails services, improve RSpec automated tests, collaborate across product and AI teams, participate in Tier 2 on-call, and shape architecture for AI agent interactions with GitLab.

Lead end-to-end product design across web and native, run user research, build rapid AI-enabled prototypes, write production frontend code, evolve the design system, and partner with PMs, engineers, and analysts to deliver delightful, outcome-driven experiences for parents.

Own end-to-end product experiences across web and native mobile: set design vision, run user research, rapidly prototype (AI-enabled), write production frontend code, evolve design systems, mentor designers, and drive measurable product outcomes.

As a Software Engineer II, you'll develop generative AI applications, enhance sales operations through AI tools, and collaborate with engineering teams on a remote basis.

Support and enhance ADI's global compliance program aligned to enterprise risk and ISO 37301. Monitor regulatory developments, update policies, execute risk‑based monitoring and testing, manage investigations and remediation, support audits, develop training and communications, track metrics, and collaborate with Legal, HR, Finance, IT, and Operations to drive continuous improvement.

Lead and support execution of ADI's global compliance programs: risk‑based monitoring, policy management, testing, investigations, training, ISO 37301 alignment, audits, remediation, and cross‑functional stakeholder coordination.

Own and improve the AI Social generative media pipeline: build and ship LLM-driven prompts/agent loops, choose and compose media (image, video, voice, music), collaborate with product/design/content, and deliver polished, production-quality social assets.

Build and maintain backend AI capabilities for GitLab Duo Chat: design flow components and agentic flows in Python/LangGraph, integrate LLMs and multi-agent orchestration, implement and maintain APIs in the Rails monolith, improve observability and reliability, and participate in on-call rotations and cross-functional collaboration to deliver safe, scalable AI chat features.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Lead and grow an engineering team for a large-scale SaaS product, providing hands-on technical leadership, code reviews, and architecture guidance. Collaborate with Product and Design to set roadmaps, contribute to implementation, hire and coach engineers, and support career development and team performance. Foster a feedback culture and adapt processes and technology, especially around AI.

As Principal Product Manager, you'll define product strategy for GitLab's AI models, focusing on custom and self-hosted AI capabilities, collaborating with engineering, and ensuring alignment with company strategy.