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. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. ABOUT THE ROLE Open to hiring remote across North America and London — we also have offices in NYC, San Francisco, Seattle, and London. We're building a tool that makes content creation easy and accessible for all types of creatives. Our users love it. Runway has an actively engaged and growing community of passionate artists and creators worldwide. And we're scaling the systems behind our support team so we can keep delivering delightful experiences as that community grows. We're looking for a Support Systems Engineer who ships production code, not tickets and specs: someone who takes a fix from proposal to merged PR themselves. This role reports directly to the Head of Customer Experience. WHAT YOU’LL DO - Own the AI support agent, our ticketing system and other Support tools end to end: authentication (JWT), response logic, routing, escalation paths and tone, tested in staging before it sees live traffic - Ship daily product changes that remove ticket volume. Recent example: extending automatic refund eligibility to one-click credit purchases, accidental upgrades and month-based proration on annual terms - Build and maintain internal CX tooling as real software, not one-offs: scripts, jobs, dashboards, admin surfaces - Run QA and evals with real test suites and pass/fail rubrics, plus monitoring and alerts for outages, bugs and volume spikes - Own releases: staged rollouts, a regression suite before every ship, clear rollback criteria, a writeup when something reaches production - Build the CX reporting the org runs on: volume, deflection, CSAT, reply and resolution time, escalation accuracy, agent spend. You own the correctness and availability of the queries. - Build and stage the guardrails on refunds, account changes and anything touching money or PII, including the audit trail - Keep the knowledge base accurate and structured for the agent to parse, and manage the handoff into the ticketing system - Keep the CX roadmap and the coverage model current, sequenced against priorities set by the Head of CX, so gaps show up before they bite - Run the day-to-day with our AI platform vendor: weekly working session, joint roadmap, issues filed with reproductions - Carry signal across teams: Product and Engineering on bugs and rollouts, Customer Education on self-serve, community on Discord and the forums, GTM and Analytics on routing and reporting WHAT YOU’LL NEED - 5+ years in Customer Experience, Support Engineering or Support Operations, with real time spent writing code - You ship production code in codebases you didn't write: read TypeScript, trace logic through someone else's service, put up a PR that survives review. Our stack is TypeScript and Node.js on AWS - Hands-on experience building and tuning AI or LLM-powered support workflows: prompt and context engineering, routing, escalation design, evals - SQL experience. You own the reporting, so you shouldn't be waiting on Analytics for it - Code-level experience with a billing or payments API: invoices, prorations, refunds. A large share of consumer tickets live here - Git, PR review, CI, staging and feature flags as your default way of working - Real QA and eval experience: you can define rubrics, build test suites and calibrate against what good looks like - Judgment about where a fix belongs, in code, in the agent or in the knowledge base - A track record carrying signal between support, product and other functions and turning it into action - Comfort managing your own work in a fast-moving environment, high ownership and high autonomy - Genuine interest in AI, creative tools or both WHAT SETS YOU APART The most successful person in this role treats the agent and the systems around it like a product they own. They watch where it fails, ship the fix and check whether it worked. They build reporting people actually use. And they show up with improvements no one asked for yet. FOR YOUR APPLICATION During our interview process, you'll have several chances to get acquainted with the Runway product and use all the features our team has built, and that starts now. As part of your application, instead of a cover letter, we ask that you try out the Runway product, specifically build a custom workflow. 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 salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. youtube.com We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator runwayml.com - GWM-1 runwayml.com - Gen-4.5 runwayml.com - General World Models runwayml.com - Robotics SDK runwayml.com - Conversational Real-time Agents runwayml.com - Runway Studios runwayml.com We're excited to be recognized as a best place to work: Crain's crainsnewyork.com | InHerSight inhersight.com | BuiltIn NYC builtin.com | INC inc.com

Requirements

Must-haves

We are building AI to simulate the world through merging art and science.
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.
Open to hiring remote across North America and London — we also have offices in NYC, San Francisco, Seattle, and London.
We're looking for a Support Systems Engineer who ships production code, not tickets and specs: someone who takes a fix from proposal to merged PR themselves. This role reports directly to the Head of Customer Experience.
Own the AI support agent, our ticketing system and other Support tools end to end: authentication (JWT), response logic, routing, escalation paths and tone, tested in staging before it sees live traffic
Ship daily product changes that remove ticket volume. Recent example: extending automatic refund eligibility to one-click credit purchases, accidental upgrades and month-based proration on annual terms
Build and maintain internal CX tooling as real software, not one-offs: scripts, jobs, dashboards, admin surfaces
Run QA and evals with real test suites and pass/fail rubrics, plus monitoring and alerts for outages, bugs and volume spikes
Own releases: staged rollouts, a regression suite before every ship, clear rollback criteria, a writeup when something reaches production
Build the CX reporting the org runs on: volume, deflection, CSAT, reply and resolution time, escalation accuracy, agent spend. You own the correctness and availability of the queries.
Build and stage the guardrails on refunds, account changes and anything touching money or PII, including the audit trail
Keep the knowledge base accurate and structured for the agent to parse, and manage the handoff into the ticketing system
Keep the CX roadmap and the coverage model current, sequenced against priorities set by the Head of CX, so gaps show up before they bite
Run the day-to-day with our AI platform vendor: weekly working session, joint roadmap, issues filed with reproductions
Carry signal across teams: Product and Engineering on bugs and rollouts, Customer Education on self-serve, community on Discord and the forums, GTM and Analytics on routing and reporting
5+ years in Customer Experience, Support Engineering or Support Operations, with real time spent writing code
You ship production code in codebases you didn't write: read TypeScript, trace logic through someone else's service, put up a PR that survives review. Our stack is TypeScript and Node.js on AWS
Hands-on experience building and tuning AI or LLM-powered support workflows: prompt and context engineering, routing, escalation design, evals
SQL experience. You own the reporting, so you shouldn't be waiting on Analytics for it
Code-level experience with a billing or payments API: invoices, prorations, refunds. A large share of consumer tickets live here
Git, PR review, CI, staging and feature flags as your default way of working
Real QA and eval experience: you can define rubrics, build test suites and calibrate against what good looks like
Judgment about where a fix belongs, in code, in the agent or in the knowledge base
A track record carrying signal between support, product and other functions and turning it into action

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Keywords to mirror

aitypescriptnode.jsawsllmsqlapigo

Platform: ashby
Effort: quick

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