Scaled Success Manager

RunwayML
Remote$150k – $190kPosted 17 March 2026

Job Description

We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. About the role *Open to hiring remote across North America — we also have offices in NYC, San Francisco, and Seattle We're looking for a systems-thinker who thrives on building scalable customer success operations from the ground up. You'll own the success of our mid-market customer segment, designing and executing the playbooks, automation, and engagement strategies that drive retention and expansion at scale. This role sits at the intersection of customer success, operations, and growth—you'll be building the infrastructure that ensures our fastest-growing customer segment receives the right engagement at the right time. What you’ll do Own the health, retention (90%+), and expansion (10-15%) of our mid-market customer portfolio, managing relationships through a combination of high-impact touchpoints and systematic engagement Build the scaled success motion from scratch—develop playbooks, automated campaigns, and engagement frameworks that can grow with the business Monitor account health and usage patterns to identify risks and expansion opportunities, then execute targeted interventions to drive outcomes Serve as the primary point of contact for mid-market accounts on renewals, expansions, and strategic questions while coordinating with Support for technical issues Design and implement automated outreach campaigns (onboarding sequences, QBRs, exec sponsor updates) that deliver value without requiring 1:1 time Identify high-potential accounts ready to graduate to enterprise-level engagement and coordinate handoffs to our Growth and Deployment team Partner with Product, Engineering, and Marketing teams to advocate for mid-market customer needs and surface insights that inform product development Establish the systems, tools, and processes needed to scale this motion beyond your individual capacity What you’ll need 4+ years in customer success, account management, or growth roles with demonstrated experience building scaled/digital customer engagement programs Track record of driving retention and expansion metrics in a portfolio management model (50+ accounts) Systems-oriented mindset—you see patterns, build frameworks, and create repeatable processes rather than one-off solutions Strong technical fluency and ability to quickly learn complex AI/creative software products Exceptional written communication skills and ability to craft compelling messaging for different audiences Bias toward action and comfort with ambiguity—this role requires building the plane while flying it Data-driven approach to decision making with ability to translate insights into action Experience in SaaS, AI/ML, or creative software industries preferred Ability to work autonomously while collaborating across Sales, Product, Engineering, and Support teams Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and sala ... (truncated, view full listing at source)
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