
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 the US — we also have offices in NYC, San Francisco, and Seattle
This is the revenue org's engineering seat and, in practice, its RevOps lead: you own CRM, enrichment tools, the signal layer, the agent fleet, and every automation that moves a record from product usage to closed-won. You write the code and create the tooling that scales productivity-per-FTE across the GTM team.
GTM Engineer means you solve operations problems with software - Python, SQL, APIs, and agentic workflows - where a traditional ops hire would file a ticket or buy another tool. This is a build role - to redesign and implement from the ground up. You treat GTM as a product that delights both our internal teams and our customers.
What you’ll do
Revenue Systems & Data Infrastructure
Own the commercial object model - routing, territories, approvals - as the schema every downstream system and agent reads from
Turn Salesforce from where reps type into where agents reconcile state, with reps inspecting and approving
Connect the stack (Salesforce, Gong, Clay, product usage, the warehouse) through APIs and webhooks so an account looks the same in every system
Build the reporting layer under the CRO dashboard: pipeline coverage, conversion rates, ramp velocity, forecast accuracy
Run it all like production infrastructure - observability, error handling, and data-quality validation - so systems get debugged, not ticketed
Agentic Workflow Engineering
Build and run the GTM agent fleet from prototype through daily production use, instrumented so decisions, failures, human edits, and downstream outcomes are visible - you own the improvement loop of evals, experiments, and iteration
Build the PLG-to-Enterprise signal layer: product usage into intent scoring into the BDR/AE routing queue
Own the Clay enrichment and outbound data infrastructure; raise BDR output at the systems level
Full-Funnel Automation
Surface the right account context to reps at the right moment: before QBRs, ahead of renewals, when an expansion signal fires
Build churn-risk and expansion detection with Deployment and CX so the post-sale motion runs on live signals
Automate deal desk mechanics: quote workflows and discount approval routing, with pricing guardrails enforced in-system
Sit with frontline sellers to find where the motion breaks, then ship the fix inside two weeks
Measurement & Iteration
Own every build end to end: discovery, prototype, rollout, adoption, iteration
Measure adoption and revenue impact of everything you ship; kill what nobody uses
Bring the VP build-vs-buy recommendations backed by working prototypes
Feed field evidence to Product so enterprise signals reach roadmap decisions
What you’ll need
6+ years across RevOps, GTM engineering, sales ops, or an adjacent applied technical discipline, with at least 3 years in RevOps or GTM engineering
Builds you can demo: Salesforce connected to adjacent GTM systems, enrichment pipelines, routing logic, agent workflows in production
Experience with data warehouses, BI tools, or event-driven systems
Clay proficiency strongly preferred; without it, show us you can get dangerous in it during the interview process
Familiarity with enterprise sales motions at $100K to $2M ACV
Analytics engineering, finance or data science background is a plus
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. 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
We're excited to be recognized as a best place to work:
Crain's | InHerSight | BuiltIn NYC | INC
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Job Details
- Department
- G&A
- Category
- Operations
- Employment Type
- Full Time
- Location
- New York City, NY (Remote)
- Posted
- Compensation
- $175,000 - $225,000 per year
About Runway
Runway is building AI to simulate the world through merging art and science. They believe world models are at the frontier of progress in artificial intelligence, changing how stories are told and how scientific progress is made.
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