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About XBOW Build the future of offensive security with XBOW. Attackers are already using AI to move faster than defenders can react—we’re creating the platform that puts security ahead in the arms race. Our AI-powered system autonomously discovers, validates, and even exploits vulnerabilities, giving organizations proof-backed results in hours instead of weeks. Founded by Oege de Moor, creator of GitHub Copilot, and backed by Sequoia, Altimeter, and other leading investors, XBOW is applying cutting-edge AI to one of the world’s most urgent problems. In just over a year, our AI, built by a world-class AI team and legendary security researchers — has uncovered thousands of real-world zero-days across the software billions rely on, and achieved the #1 ranking on HackerOne’s global leaderboard. We’re a team of builders, hackers, and researchers who thrive on solving problems others think are impossible. If you want to push the boundaries of AI, reshape how security is done, and join the group defining this new era of defense — we’d love to talk. Your Role We’re looking for a Software Engineer with deep expertise in LLM prompting, orchestration, and software engineering. In this role, you’ll design and implement systems that coordinate large language models with real-world tasks, advancing the intelligence at the heart of our platform. You’ll collaborate with our AI, Engineering and Security teams to create novel prompting strategies, build orchestration layers, and deliver production-ready systems in TypeScript. This role is for someone who thrives in a fast-moving, research-driven environment and enjoys turning ambiguous ideas into robust, scalable solutions. What You'll Do Build LLM-powered software that actually works, by designing prompt flows and orchestrations that ensures great performance with no false positives. Architect and build an AI-powered software stack that is production-grade, testable and maintainable. Design and build experiments and evaluation frameworks for performance testing of the system at scale. Conduct data analysis to draw conclusions. Collaborate with the rest of the AI team, with security experts, and both frontend and backend developers to create end-to-end systems that work and customers love. Own projects end-to-end: from basic ideation and experimentation to deployment and production monitoring. Continuously conduct research on how to harness the advancements in LLMs to make our system better and faster. Who You Are Strong experience with building software around LLMs: prompting, agentic orchestration, fault-tolerance, and integration of LLM parts with hard-coded logic. Strong software engineering skills: architecting and building production-grade software that runs reliably and can be maintained. Experience with TypeScript or proven ability to learn a new programming language quickly. Strong skills in structured and independently-driven problem-solving. Able to work with incomplete information and rapidly testing hypotheses. Comfortable with an energetic environment that mixes the fast-paced agile prioritisation of a startup with the curiosity mentality of a research lab. Eager to own projects and jump into the deep end, learning as you go. Curious, adaptable and collaborative. MSc or equivalent or higher in computer science, math, physics or machine learning. Bonus If You Have Prior experience with the security sector, especially involving offensive security and/or applying LLMs in a security context. Contributions to open-source software, particularly within applications of or frameworks for LLMs. Strong theoretical background, e.g. a Ph.D in machine learning, computer science or math. Startup experience and comfort with ambiguity. What We Offer Compensation & Equity: Competitive salary and a generous equity package, making you a true owner of the company. Career Growth: Shape your role, lead the function, and grow with the company as we redefine cybersecurity. Meaningful Work: You will tackle technically complex challenges and play a pivotal role in the growth of our business, working alongside an amazing team and some of the world’s experts to shape how AI transforms cybersecurity. What Else You Should Know Location: Remote (all team members are remote but we meet regularly and you’re supported to travel to collaborate with colleagues in person) Contract: Full-time. Hiring Process: 45-min introductory chat with our Talent team. 45 minutes with one of our Engineering Leads. 2-3 hour technical deep dive around relevant case study. 30-min final meeting with the Engineering Lead for the assigned team. We aren't focused on seniority titles at XBOW—so if you’re worried about “leveling,” don’t be. We care a lot more about mission fit, capability, and impact than what’s on your LinkedIn headline. We believe in people who are driven by curiosity and a willingness to learn. Even if you don't check every box, we encourage you to apply if you're excited about the role and our mission.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.