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Director, Growth Marketing

League
Remote remote· Marketing & Sales August 15, 2026
Full-Time
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Full-TimeMarketingLeaguehealthpipelinetoolsrangeGrowthCanadasalesstackjust

About the role

About League League is one of the fastest-growing technology companies in Canada and the leading healthcare experience platform. Getting healthcare is often the easy part — finishing it is where things fall apart: people book the appointment and skip the follow-up, fill the prescription and stop taking it, get the referral and never make the call. That gap costs health plans and health systems money, and it costs people their health. League closes that gap — identifying what each person needs to do next, clearing what’s in their way, and getting it done, for the 70 million+ people whose care already runs through our platform. Health plans and health systems trust us to do this at scale. Organizations like Manulife, SCAN, Geisinger, and Medibank on the payer side, and Baptist and Shoppers Drug Mart on the provider side. Position Summary: This is a builder role, not a maintainer role — equal parts strategy and execution. You're the most senior growth marketing hire on a team that's re-building its demand generation engine. You'll have the budget, a team, and direct access to leadership to do it. You'll be marketing into two of the most sought-after B2B buyer groups in health tech: payers with long procurement cycles and multiple clinical/financial stakeholders, and providers balancing patient experience against margin pressure. If you want to prove you can build and run demand gen at enterprise scale, in a category where the sales cycle actually tests your craft, this is that proving ground. You're inheriting a full, well-funded MarTech stack — Salesforce, Pardot, Bizible, Demandbase, and Qualified — and the website itself, but the job isn't to just run any of it as-is. We want someone who rebuilds how that stack operates to be agentic-first: designing AI agents that pull signal to plan campaigns, launch and sequence them across channels, and continuously test and optimize without manual hand-offs between tools. What You'll Do: Own and optimize our tech stack and website Own pipeline generation across paid search, paid social (LinkedIn), SEO, content, lifecycle/email, and account-based marketing Continuously test messaging, creative, and campaign structure — and bring examples of non-boilerplate campaigns that actually moved pipeline Own reporting: define KPIs and dashboards, and keep pipeline numbers trusted by Sales Own the AI-Native Workflow strategy and AI Engine Optimization (AEO): as buyers increasingly use LLMs to research vendors, you have ideas on how to build League's presence in those results Strategically partner cross-functionally with Sales, Product Marketing and Revenue Operations Security-Related Responsibilities Compliance with Information Security Policies Ensure access management is performed in compliance with the employee's role and responsibilities Responsibility and accountability for executing League's policies and procedures within the department/ team Notification of HR, Legal, Compliance & Security of any incidents, breaches or policy violations What You'll Bring: 7+ years in B2B demand generation or growth marketing, with real ownership of pipeline outcomes — not just campaign support Enterprise background: you've marketed to large, complex organizations with long sales cycles and multiple stakeholders; payer or provider experience is a strong plus Hands-on across the full stack: paid search, paid social (LinkedIn), SEO, content, and account-based marketing Fluent in the pipeline metrics that matter here — MQL/SQL/SQO conversion, pipeline contribution, cost per opportunity — not just CAC/LTV/ROAS Real experience building AI agents or automations, not just prompting a chatbot — bonus if you already gravitate toward MCP-first, Salesforce-native tools Strategic and hands-on: you're equally excited to set the plan and execute it Bonus: experience with ABM platforms like Demandbase or 6sense Bonus: experience in HealthTech, FinTech, InsurTech, or other large enterprise-focused products CANADA APPLICANTS ONLY: The Canada-specific compensation range below for this full-time position is exclusive of bonus, equity and benefits. This range reflects the minimum and maximum target for base salaries for the position across all Canadian locations. The salary range is intentional to account for the performance and career progressions a Leaguer will experience in the role throughout their time at League. Where in the band you may land is determined by job-related skills/experience. Your recruiter can share more about the specific salary range specific to your skills and experience during the hiring process. Compensation range for Canada applicants only $145,000—$170,000 CAD AI Fluency & Ways of Working At League, we are an AI-native organization . We expect all employees regardless of role or level to thoughtfully leverage AI to improve the quality, speed, and impact of their work. What this means in practice: Use AI tools as part of your daily workflow to enhance productivity, problem-solving, and decision-making (e.g., drafting, analysis, coding, research, or process automation) Apply judgment and accountability when using AI by reviewing outputs for accuracy, bias, and quality before use Continuously learn and adapt as new AI tools and capabilities emerge, incorporating them into your ways of working Identify opportunities to improve how work gets done from personal productivity to team-level workflows by leveraging AI effectively Operate with strong data responsibility and security awareness , especially when working with sensitive or regulated information How this scales by level: Individual Contributors: Use AI to improve personal productivity and quality of output Senior ICs / Managers: Integrate AI into team workflows and improve processes Leaders: Drive AI adoption at the organizational level and shape how work is done across teams What we look for: Demonstrated experience using AI tools in a practical, responsible way Curiosity and openness to experimenting with
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