Top AI Jobs in Vancouver

Develop and execute growth marketing for enterprise AI systems by translating technical work into compelling stories, videos, demos, and case studies. Shape company positioning, own social and content channels, build marketing tools and agentic workflows, track pipeline impact, and run experiments. The role combines strategic marketing, business storytelling, content creation, coding, and AI research.

Join Welo Data’s global contributor network for flexible, remote AI projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and requirements provided before each assignment.

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.

Develop and execute go-to-market strategy for AI products: define positioning and messaging, conduct market and competitive analysis, enable sales, coordinate launches, gather customer insights, and measure product performance.

Own client relationships and account health for complex social media operations. Translate client goals into clear briefs, coordinate planning, publishing, community management, reporting, approvals, and handoffs, and resolve delivery issues. Improve workflows using AI tools and agentic processes, review AI-generated work critically, interpret performance data, protect service quality, track scope and capacity, and communicate recommendations and risks clearly across clients and internal teams.

Write and refine on-brand social copy across major platforms, engage fan communities, fact-check content, maintain brand voice guidance, and identify timely cultural opportunities. Use AI agents and reusable workflows to create variants, perform checks, summarize community themes, and improve team processes. The role requires strong editorial judgment, platform awareness, excellent written English, accessibility and accuracy expertise, reliable collaboration, and demonstrated hands-on experience using AI tools beyond basic chatbot prompting.

Own new business and account growth across hyperscalers, neoclouds, enterprises, and frontier AI labs in the Americas. Manage complex technical sales cycles, layered OEM/ODM and channel routes, capacity commitments, design-ins, pipeline forecasting, contracts, and executive relationships. Translate semiconductor performance, power, and TCO advantages into commercial outcomes while partnering with product, engineering, marketing, legal, and finance. Build a qualified pipeline through an existing customer network and represent the company at industry events.

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.

Conduct original research on reliable agentic AI, developing methods for simulation, evaluation, optimization, regression control, and continuous learning. Analyze agent failures, traces, and human feedback; create experiments and prototypes; and translate research into production-facing systems. Collaborate with product and engineering teams, contribute to technical strategy, and provide rigorous experimental evidence. The role requires strong research depth, publication or open-source contributions, hands-on Python development, and expertise in LLM agents or agentic systems.

Own the company’s AI-powered quality and release infrastructure as its first dedicated hire. Build agent-run test harnesses, LLM graders, regression coverage, release gates, fresh-install and upgrade verification, and natural-language UAT. Manage CI health, artifact publication, deployment pipelines, credentials, certificates, and staging environments. Write production Python code, convert escaped bugs into regression tests, and provide trusted release-readiness evidence through dashboards, runbooks, retrospectives, and operating policies.

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.

Lead Strata from inception as co-founder, defining the vision for regulatory intelligence software, engaging enterprise customers, shaping the product roadmap, providing technical leadership for trusted AI agents, and recruiting teams across go-to-market, product, engineering, and customer success. The role requires early-stage B2B SaaS experience, hands-on LLM and agentic architecture expertise, and the ability to build products emphasizing accuracy, citations, auditability, and expert review.

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.

Build and deploy internal AI tooling, agents, integrations, and workflows that improve productivity across engineering, research, and business teams. Evaluate emerging AI tools and models, develop observability and responsible-use guardrails, and partner with stakeholders to prototype and scale solutions. Drive adoption through documentation, enablement, and hands-on support while integrating AI into autonomy, simulation, ML training, and business workflows.

Serve as the technical sales and customer-facing expert for an AI platform. Responsibilities include conducting product demonstrations, supporting proofs of concept, advising on architecture and development, planning professional services projects, tuning retrieval and agentic pipelines, responding to RFPs, supporting customer adoption, and communicating product feedback internally. The role requires strong AI, cloud, on-premise, application development, storytelling, and enterprise customer engagement experience.

Provides technical leadership for agentic AI, ontology, knowledge graph, semantic, and enterprise data platform architecture. Designs reusable data models, ingestion pipelines, integrations, entity resolution, schema alignment, validation, and agent workflows across supply chain systems. Evaluates emerging technologies, establishes architecture and governance standards, mentors teams, and translates research into scalable product capabilities.

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.

Partners with AI labs to integrate models, run evaluations, deliver results, and manage customer relationships. Builds pragmatic full-stack solutions, automations, onboarding workflows, and delivery tooling for cutting-edge AI teams. Translates customer and research feedback into product and engineering initiatives, supports strategic account growth, and serves as a technical point of contact across onboarding, releases, and issue resolution.

Own end-to-end AI product development for enterprise clients, from requirements and rapid LLM prototyping through production deployment. Responsibilities include data modeling, ETL pipelines, integrations, evaluation, observability, security, reliability, cost management, and client communication. The role requires shipping real AI products, iterating based on usage, and independently managing ambiguous technical and product decisions.

Build and scale AI-agent infrastructure, including orchestration, tool calling, context management, guardrails, evaluations, and LLM-as-judge pipelines. Develop Python and Node.js microservices, Laravel APIs, AWS infrastructure, and optimized MySQL systems. Diagnose agent failures, improve prompts and tools, maintain reliability and observability, contribute to architecture, review code, collaborate cross-functionally, and mentor engineers.

Partner with executives to understand business operations, identify and prioritize high-impact AI opportunities, define ROI, and create actionable roadmaps. Collaborate with engineers to scope solutions, inform architecture, maintain alignment with business outcomes, present recommendations to C-suite stakeholders, and manage handoffs to implementation.

Leads complex government AI deployments from pre-sale discovery through production adoption, overseeing client relationships, delivery planning, cross-functional execution, change management, and executive communication. Translates agency workflows into technical requirements, manages risks and dependencies, drives measurable outcomes, and converts deployment feedback into product improvements. Builds deployment playbooks, operating cadences, and future delivery teams while supporting renewals and expansions. Requires strong AI/ML and enterprise systems fluency, senior stakeholder leadership, and 30–50% travel.

Supports responsible AI governance by developing policies, maintaining control frameworks, conducting AI risk assessments, monitoring regulatory compliance, preparing reports, and advising legal, compliance, security, AI, and business stakeholders. The role also tracks governance metrics, supports audits, researches emerging regulations, and recommends improvements to AI governance programs.