About the job
About XBOW
Join XBOW in shaping the future of offensive security. As attackers leverage AI to outpace defenders, we are committed to developing a platform that leads the charge in this critical arms race. Our innovative AI-driven system autonomously identifies, validates, and even exploits vulnerabilities, providing organizations with verified results in a matter of hours instead of weeks.
Founded by Oege de Moor, the visionary behind GitHub Copilot and supported by prestigious investors including Sequoia and Altimeter, XBOW is addressing one of the most pressing challenges of our time using state-of-the-art AI technology. Within just a year, our AI, crafted by a premier team of AI specialists and elite security researchers, has revealed thousands of actual zero-day vulnerabilities in the software upon which billions depend, securing the top spot on HackerOne’s global leaderboard.
We are a dynamic collective of builders, hackers, and researchers who relish tackling challenges deemed impossible. If you are eager to push the limits of AI, redefine security protocols, and be part of a pioneering team in this new era of defense, we want to hear from you.
Your Role: Software Engineer - AI Systems
We are in search of a Software Engineer with profound knowledge in large language model (LLM) prompting, orchestration, and software engineering. In this pivotal role, you will design and implement systems that synchronize LLMs with real-world tasks, enhancing the intelligence at the core of our platform. You will work closely with our AI, engineering, and security teams to devise innovative prompting strategies, construct orchestration layers, and deliver production-ready systems using TypeScript.
This position is ideal for an individual who flourishes in a fast-paced, research-oriented setting and enjoys transforming nebulous concepts into robust, scalable solutions.
What You Will Do
Develop LLM-powered software that performs effectively by designing prompt flows and orchestrations that ensure optimal performance without false positives.
Architect and construct a production-grade AI-powered software stack that is testable and maintainable.
Design and implement experiments and evaluation frameworks for comprehensive performance testing of the system at scale. Conduct data analysis to derive insights.
Collaborate with the AI team, security experts, and both frontend and backend developers to create cohesive end-to-end systems that deliver value to customers.
Take ownership of projects from inception and experimentation through deployment and production monitoring.
Engage in ongoing research to enhance the capabilities of AI systems.
