Detection & Response Engineer
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 — we also have offices in New York, San Francisco, Seattle, London, Paris, and Tel Aviv.
Runway is hiring a Detection & Response Engineer to own how we find and stop attacks against our infrastructure, our research environment and our products.
Securing a company that trains and serves frontier video models is a different problem from securing a typical SaaS product. The environment includes research compute, large training datasets, a fast-moving build pipeline and engineers who work inside AI-assisted tooling every day. Each of those changes what an attack looks like and what you need to see to catch it.
You'll join the Security team and build our detection and response program the way an engineer would: detections as code, response as automation, evidence as something you can query. This is a role with real ownership: you'll own the detection program end to end, from what we log to how quickly we close an incident. You'll report to the head of security, partner with engineers across platform and research, and shape how this function grows from here.
What you'll do
Own detection and response end to end: what we log, what we alert on, how we triage and how we recover
Write and tune detections as code across multiple cloud environments, Kubernetes, identity systems, endpoints and SaaS, and measure them on coverage and precision rather than alert volume
Lead incident response from the first alert through containment and forensics, then write the post-incident review people actually read
Build automation that takes toil out of triage, including enrichment, correlation, containment actions and evidence collection, and use LLM-based tooling where it holds up under audit
Monitor AI agents and developer tooling operating inside our environment, and turn that into concrete telemetry and controls
Partner with platform and research engineers so new systems ship with logging and response playbooks in place on day one
Run threat hunts and tabletop exercises against the parts of the environment that worry you most, and fix what you find
Turn incident and detection metrics into evidence for SOC 2, ISO 27001 and enterprise customer security reviews, working with our GRC team
Participate in an on-call rotation for security incidents
What you'll need
Hands-on incident response experience: you've triaged live alerts, led investigations and written up what happened afterward
Experience building and tuning detections in a modern SIEM, ideally managed as code
Working knowledge of how attackers move through cloud and Kubernetes environments (IAM abuse, container escape, credential theft, supply chain compromise) and what that leaves behind in logs
Comfort writing Python, Typescript, Rust or another language to automate response work and connect security tools
Familiarity with at least one major cloud platform and with Kubernetes at the level of audit logs, RBAC and workload identity
Clear writing. Incident timelines, detection documentation and updates to leadership are all part of the job
Judgment about what to alert on, what to automate and when to wake someone up
Even better if you have
Experience monitoring GPU or HPC-style infrastructure, or research environments with large datasets
Experience building detections or guardrails for AI agents, LLM tooling or MCP servers
Cloud forensics experience: disk and memory acquisition, cloud audit trail reconstruction, chain of custody
Published open source detection content
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
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