Top AI Jobs in Vancouver

Lead the design, delivery, and operationalisation of agentic AI workflows and agents from discovery to production. Build integrations with enterprise systems, reusable automation patterns, and monitoring frameworks while partnering with stakeholders and evangelising safe, auditable AI automation across the business.

Lead product strategy, portfolio execution, and AI-first transformation for Colliers’ proprietary commercial technology platforms. Oversee multiple Product Management teams, establish roadmaps and FED governance, partner with Data, AI, Engineering, and global business leaders, and deliver enterprise B2B products for sales and services professionals. Drive adoption, product telemetry, KPIs, ROI measurement, and AI-enabled workflows using cloud and analytics technologies.

Manage end-to-end IT and indirect procurement, including intake, sourcing, supplier evaluations, negotiations, contract management, renewals, spend tracking, compliance, and supplier performance. Partner with stakeholders to develop procurement strategies, identify savings, mitigate risk, improve processes, and standardize tools and reporting across technology, professional services, and other categories.

Leads Scribd’s content intelligence and UGC supply portfolio, owning corpus classification, metadata, quality, gap analysis, AI infrastructure, contributor experiences, and content acquisition strategy. Partners with ML, engineering, data science, consumer product, and business development teams to connect content supply with business value. Manages senior product leaders and established engineering and analytics programs while setting portfolio roadmaps and representing content strategy with executives.

Own the function’s AI transformation strategy, prioritize high-impact opportunities, map workflows, and drive measurable adoption. Build and manage AI agents using no-code and low-code tools, configure skills and MCP connections, evaluate agent performance, and iterate solutions. Lead change management, champion networks, cross-functional collaboration, intake processes, and alignment with Enterprise AI and executive stakeholders.

Build and deploy agentic and generative AI systems that automate risk and compliance investigations. Own full-stack ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based modeling across transaction, graph, text, and profile data. Collaborate with product, engineering, platform, and operations teams while leading strategic roadmaps and delivering scalable production systems.

Build and deploy agentic and generative AI copilot and autopilot systems for risk and compliance automation. Own end-to-end ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based model development. Collaborate with product, engineering, platform, and operations teams to improve fraud detection and analyst productivity. Drive strategic roadmaps and cross-functional programs with significant business impact.

Lead global sales enablement programs that drive measurable revenue by diagnosing performance gaps, creating role-based training and playbooks, aligning cross-functionally, and optimizing adoption through analytics and manager-led reinforcement.

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.

Build and ship production-grade agentic AI workflows across Acquia’s digital experience platform. Design stateful multi-agent systems using LangGraph, Temporal, and Pydantic; own LangFuse observability, evaluation, and benchmarking; establish standards for RAG, prompting, context optimization, and tool calling; partner on secure, reliable enterprise architectures; evaluate AI tooling; mentor engineers; and support customer architecture and roadmap discussions.

Lead scientific and strategic AI efforts for Vaccines Medical: define AI vision and roadmap, govern responsible AI standards, prioritize and deliver validated AI-enabled solutions, partner cross-functionally, oversee deployment and adoption, manage budget and vendors, and ensure regulatory, ethical, and scientific compliance across global medical affairs.

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.

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 end-to-end UX across Babylist web and mobile: run user research, build rapid interactive prototypes, write production front-end code, evolve the design system, instrument outcomes, and champion AI-native design workflows to create intuitive, delightful experiences for families.

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.

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.

Develops, calibrates, validates, and maintains credit risk models, including PD, LGD, and EAD models, for lending, collections, loss forecasting, capital planning, and stress testing. Analyzes large datasets, evaluates model performance, documents model changes, supports systems testing, and communicates statistical insights to stakeholders and management. Collaborates across the credit union to improve risk-return strategies and reporting.

Identify business challenges and translate them into AI initiatives; architect AI solutions using appropriate models, frameworks, and infrastructure; guide data science and engineering teams through proof-of-concept development and deployment; mitigate bias and model drift through monitoring; and communicate an AI vision aligned with business goals.

Lead ShipMonk’s global talent acquisition function across high-volume warehouse hiring, corporate and technology recruiting, and senior searches. Build scalable, data-driven recruiting systems, define hiring metrics, coach recruiters, train hiring managers, shape the talent brand, and introduce AI-enabled recruiting tools. Initially serve as a hands-on player-coach before transitioning to broader team leadership. Travel 25–30% across fulfillment sites and corporate offices.

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 Sierra’s largest and most complex enterprise sales opportunities across business units and geographies. Build trusted C-suite relationships, structure multi-million-dollar deals, manage risk and pricing, engage customers alongside founders, and shape strategic account and sales strategy. Use AI tools throughout the sales cycle for research, outreach, forecasting, summarization, and deal execution. The role requires executive-level communication, precision, and experience closing complex six- and seven-figure ACV deals.

Build LanceDB’s revenue marketing function and enterprise demand engine from the ground up. Own account-based marketing strategy, segmentation, campaigns, content, account planning, martech implementation, pipeline reporting, and partner co-marketing. Identify high-intent accounts through open-source and product-usage signals, create tailored omnichannel programs, and collaborate closely with founders, Sales, RevOps, and Partners to source and influence enterprise pipeline.

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 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.

Serve as the primary technical advisor for SMB sales opportunities, partnering with Account Executives throughout sales cycles. Lead technical discovery, product demonstrations, proof-of-value engagements, competitive evaluations, security questionnaires, RFPs, and technical documentation. Advise IT, security, developer, DevOps, and executive stakeholders on identity, endpoint, SaaS, secrets, cloud, and AI security solutions. Collaborate cross-functionally to improve demos, playbooks, enablement, and customer education.