Top AI Jobs in Vancouver

Leads Absorb’s product management organization, translating company strategy into product roadmaps, portfolio investments, and measurable outcomes. Oversees PM team development, operating models, governance, customer advocacy, capacity planning, and cross-functional delivery across product pods. Drives practical AI adoption in product workflows, establishes measurable adoption goals and guardrails, and strengthens strategic product management capabilities. The role requires extensive B2B SaaS product leadership and experience scaling high-performing PM teams.

Develop AI/ML strategy and production software for Smile Digital Health’s healthcare data platform. Design architectures and implement semantic matching, RAG, document parsing, agentic systems, knowledge graphs, and evaluation workflows. Write clean, tested, documented code, integrate external components, conduct reviews, collaborate with clients and product teams, contribute to technical strategy, and mentor developers in an Agile environment.

Own strategic territories and close net-new enterprise software deals. Lead value-based sales cycles from discovery through proof of value, negotiation, and close; build executive relationships; develop account strategies; maintain Salesforce pipeline and forecasts; partner with alliances teams; and advise customers on supply chain resilience, risk, and compliance.

Supports the GTM Lead and founders across sales, growth, and content. Responsibilities include creating technical content for AI products, running growth experiments, supporting outbound initiatives, building the sales funnel, communicating with technical buyers, and collaborating with engineering in an early-stage environment.

Build Lingopal’s go-to-market motion for its evolving AI agent platform. Develop positioning, target accounts, outbound strategy, sales processes, and pricing inputs. Own enterprise sales from prospecting through discovery, pilots, and closing across customer-support-heavy enterprises and scaling AI-agent companies. Engage senior buyers including Chief AI Officers, COOs, and CTOs, while feeding market insights back into product strategy.

Architect, build, deploy, and operate production-grade AI agentic systems and workflows. Responsibilities include backend and full-stack development, agent orchestration, workflow state, retrieval, memory, approvals, failure recovery, data architecture, enterprise integrations, cloud infrastructure, observability, security, and scaling. The role establishes reusable engineering patterns and partners with users to deliver reliable AI products, while addressing production issues involving model behavior, permissions, latency, cost, and consistency.

Design and build real-time, highly concurrent software and cloud-native systems for an AI-powered emergency communications platform. Integrate and deploy LLMs, optimize voice and audio-processing pipelines, and support speech recognition, synthesis, detection, and filtering. Contribute to infrastructure, observability, security, scalability, and fault tolerance. Provide technical leadership through architecture decisions, code reviews, mentoring, and engineering best practices.

Le directeur ou la directrice dirigera la stratégie, la feuille de route et l’équipe de gestion de produits axées sur la croissance des vendeurs et des marchands. La personne optimisera la distribution, la découverte, la conversion et les ventes sur des plateformes de marché et d’infonuagique, établira des partenariats stratégiques et mobilisera les équipes d’ingénierie, de ventes, de marketing, de finance et de réussite client. Le rôle exige une solide expérience commerciale, du leadership produit et une expertise des écosystèmes technologiques.

Lead AI transformation across Sales, Marketing, Customer Success, Partnerships, and Revenue Operations. Identify high-value opportunities, design and deploy production AI agents, agentic workflows, automations, integrations, and enterprise solutions, then drive adoption and measure business impact. Partner with functional leaders, make sound decisions about AI suitability, redesign operating models, improve reliability and governance, and mentor colleagues while establishing reusable standards across the organization.

Build and maintain the TypeScript-based Duo Client SDK, including Node.js core packages, public APIs, browser-compatible modules, Vue 3 client components, and platform adapters. Responsibilities include migrating consumers from the GitLab Language Server, managing versioning and deprecation paths, strengthening credential security, optimizing browser performance, writing tests, conducting code reviews, and participating in on-call support.

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 maintain secure, scalable Flow Registry features for GitLab’s agentic platform using Python, LangChain, and LangGraph. Design GraphQL and REST APIs, improve automated testing, optimize PostgreSQL-backed applications, and collaborate across backend, frontend, product, UX, and AI teams. Participate in Tier 2 on-call support, troubleshoot production issues, improve observability, and contribute to responsible AI integration in GitLab’s remote, asynchronous environment.

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 the enterprise readiness and platform modernization strategy for SaaS Manager. Own product strategy, roadmap, prioritization, customer discovery, technical architecture decisions, integrations, data ingestion, reliability, administration experiences, and responsible AI capabilities. Collaborate across Product, Engineering, Design, Security, Privacy, Analytics, and go-to-market teams to define milestones, measure outcomes, manage dependencies and risks, coordinate launches, and iterate based on customer feedback.

Build and operate Kraken’s internal AI platform, including governed integrations, authentication, internal tooling, evaluation systems, spend controls, identity and access controls, provisioning, vendor configuration, and policy enforcement. Provide technical enablement through documentation, deep dives, and office hours while supporting teams and administering the enterprise AI estate.

Lead positioning, messaging, go-to-market strategy, launches, channel enablement, competitive intelligence, and analyst relations for Sophos’ AI cybersecurity solutions. Translate complex technical capabilities into buyer- and partner-focused narratives, build launch assets and sales tools, and coordinate cross-functional execution across product, sales, marketing, and research teams. The role also develops customer feedback loops, competitive battlecards, and category-defining market perspectives.

Define and execute Firefox Desktop search strategy across Windows, macOS, and Linux. Own search roadmaps, experimentation, engagement and revenue metrics, AI-powered search experiences, partner commitments, and cross-functional delivery. Balance user experience, privacy, technical constraints, and business outcomes while collaborating with Engineering, Design, Research, Data Science, and Business Development.

Own client-facing digital product engagements from discovery through delivery, including AI agent development, greenfield product builds, legacy platform modernization, and AI-native enablement. Translate ambiguous needs into PRDs, roadmaps, success criteria, and shippable work. Partner with engineers on agent architecture, evaluations, and guardrails; manage multiple clients, scope, budgets, timelines, steering committees, and ROI outcomes. Provide streaming and OTT media product expertise while contributing to internal delivery practices.

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 deploy enterprise automation and AI solutions across business systems, data platforms, and IT environments. Analyze business processes, identify automation opportunities, integrate platforms and APIs, test and monitor production solutions, and support adoption through documentation and training. The role requires hands-on coding, AI workflow experience, process analysis, and the ability to translate business needs into secure, practical technical solutions.

Lead go-to-market strategy and launches for an agentic AI business unit serving regulated life sciences buyers. Develop product positioning, messaging, narratives, sales enablement, campaigns, and customer-facing value propositions. Partner with Product, Sales, Demand Generation, and Revenue Operations, track pipeline and revenue impact, and use AI tools to streamline marketing execution. The role requires B2B SaaS or technology marketing experience, strong technical writing, product launch expertise, and cross-time-zone collaboration.

Design and implement end-to-end AI systems and production-grade components. Build and maintain RAG pipelines, backend services, APIs, and data pipelines. Write Python code using Azure AI SDK. Implement document digitization, vectorization, semantic search, and content summarization. Prepare training/evaluation datasets, participate in code reviews, and drive engineering quality and deployment of AI-powered SaaS workflows.

Lead AI strategy and architecture engagements, design AI operating models, and facilitate executive communication while ensuring successful implementation with a Forward Deployed Engineer.

Lead the design and delivery of Agentic AI solutions to enhance customer experience and operational efficiency, focusing on enterprise-wide AI transformation.