Top AI Jobs in Vancouver

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.

Support customer deployments and adoption of Regology by serving as a technical subject matter expert and project manager. Lead enterprise integrations, API discussions, AI-related technical conversations, training, troubleshooting, and requirements translation across customers, product, engineering, and sales teams. Coordinate implementation activities, resolve integration issues, and provide technical support during customer and sales engagements.

The VP of Engineering will own engineering strategy, architecture, scaling, hiring, performance management, and people development. This hands-on leader will write and review code, establish technical direction across two pods, develop engineers into technical leads, represent engineering to executives, and partner cross-functionally to prioritize and deliver critical work. Experience in healthcare, HIPAA, or SOC 2 environments is preferred.

Leads 1Password’s analytics engineering function, owning data architecture, roadmap, modeling, semantic layers, BI tooling, pipelines, governance, testing, documentation, and data quality. Manages and develops analytics engineers, establishes technical standards, reviews complex dbt and SQL work, optimizes warehouse performance, and partners with senior leaders across Finance, Marketing, Product, Analytics, and Data Engineering. Builds trusted data foundations supporting company-wide decisions, AI initiatives, and generative BI.

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.

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.

Own and improve a portfolio of knowledge assets, including articles, SOPs, workflows, playbooks, and enablement materials. Create structured, discoverable, AI-ready content for Customer Success teams and AI-powered support experiences. Partner with Product, AI, Data, and subject matter experts to document changes, maintain content quality, support learning in the flow of work, and use customer, search, QA, and AI performance insights to drive continuous improvement.

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.

Owns full-cycle enterprise and mid-market sales for an AI cloud inference platform, from prospecting and discovery through technical demonstrations, proposals, negotiation, and close. Builds relationships with CTOs, ML engineers, and infrastructure leaders; develops pipeline, forecasts accurately, maintains HubSpot CRM hygiene, expands existing accounts, represents the company at industry events, and collaborates with product, engineering, CRO, founders, BDRs, and DevRel to strengthen the go-to-market motion.

Build and operate scalable full-stack features for Evisort’s AI-driven contract management platform. Collaborate with engineering, data science, product, and design teams to deliver user-centric SaaS solutions. Own functional areas from development through production, apply strong engineering and DevOps practices, contribute to roadmap and architecture decisions, mentor teammates, and translate complex problems into clear solutions in an agile environment.

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.

Own AI agent evaluation frameworks and deployment across Core Financials. Lead benchmark development, customer and ecosystem discovery, API and data-service integrations, cross-agent standards, and scalable self-service product frameworks. Partner with engineering, UX, research, finance leaders, and audit firms to translate requirements into production capabilities. Manage feature delivery, resolve technical dependencies, align stakeholders, communicate results to executives, and support monetization of Workday’s Financials AI portfolio.

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.

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.

Manage the end-to-end sales process for existing financial services clients, focusing on upselling hedge funds, asset managers, investment banks, and sell-side research teams. Responsibilities include prospecting, pipeline development, product demonstrations, trials, relationship management, forecasting, closing sales, and meeting targets. The role partners with marketing and product teams, gathers client feedback, and requires regular client travel.

Build AI-native quality engineering capabilities by developing UI and API test automation, LLM-powered agents, and reusable self-healing frameworks. Integrate traditional and agent-generated tests into CI/CD pipelines, assess test reliability, optimize agentic workflows for cost and latency, implement retry and fallback strategies, troubleshoot independently, document processes, and communicate results to stakeholders.

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.

Design, build, and operate production AI systems and marketing data infrastructure. Develop retrieval pipelines, agent orchestration, CDP integrations, ETL/ELT pipelines, and analytics. Automate workflows with AI, ensure data quality and reliability, partner with stakeholders, ship Python and SQL code, mentor engineers, and drive requirements to production.

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.

Lead development and deployment of production-grade generative AI applications for sales enablement. Build copilots, automated outreach, and voice/chat interfaces; work across model experimentation, app development, and infrastructure; partner with revenue ops, product, and engineering to scale AI features that improve efficiency and personalization across the sales funnel.

Build and ship end-to-end ML/AI systems (traditional ML, NLP, LLMs/AI agents) on transaction, merchant, and location data. Prototype, productionize, and monitor models, collaborate with engineering and product, and (for senior hires) shape roadmap and mentor teammates.

Establish and lead IFS Copperleaf’s applied AI and data science practice. Build classical predictive models, LLM and agentic AI capabilities, curated datasets, evaluation frameworks, and production ML pipelines. Own model deployment, monitoring, drift detection, retraining, governance, and quality standards. Provide hands-on technical leadership, mentor engineers and scientists, guide RAG and fine-tuning initiatives, and translate ambiguous product needs into explainable, defensible AI solutions for regulated capital planning.

Lead and grow a solution engineering team for AI-powered Dynamics 365 business solutions. Own technical win strategy, coach demos and solution design, partner with sales to convert pipeline, enable value assessments, manage proposals, and align with partners and Customer Success to achieve revenue and deployment outcomes.

Leads enterprise account growth for Neocloud and emerging AI infrastructure customers. Develops strategic account plans, identifies and closes new business, manages executive stakeholder relationships, coordinates suppliers and internal teams, and drives solution development across data center power, cooling, connectivity, security, and scalability needs. Tracks opportunities, renewals, and customer plans while coaching sales teams on strategic engagements.