About Irregular
Irregular is the first frontier security lab with the mission of protecting the world in the time of increasingly capable and sophisticated AI systems. We build next-generation defenses through high-fidelity research platforms that simulate and monitor real-world AI security scenarios.
As AI systems become more powerful, we focus on staying ahead of emerging threats and vulnerabilities, ensuring these transformative technologies can be deployed safely and securely.
As a Software Engineer at Irregular, you will take ownership of designing, building, and scaling the production systems that power our evaluation and security platform for frontier AI models.
Your work will focus on creating robust, resilient, and high-performance infrastructure—whether that’s distributed pipelines, backend services, or tooling that supports our research teams.
This role is engineering-first with a strong research and cyber component. You will develop systems that must run reliably in production, integrate with external partners, and support large-scale data, experiments, and automated evaluations. You’ll drive architectural decisions, lead technical implementations, and shape how our platform evolves.
עיקרי התפקיד
Architecting and scaling production-grade systems and workflows.
Building backend services, APIs, and monitoring tools for large-scale model evaluations.
Designing infrastructure that supports research experiments at scale.
Implementing agent frameworks in production environments
Designing and building challenges that measure a model’s ability to evade discovery, allowing us to see if models can operate on remote systems while avoiding detection by common defensive security tools.
You may be a good fit if you:
Have strong software engineering fundamentals and multiple years of production experience.
Have experience working in multidisciplinary teams, and can adapt to rapidly evolving challenges.
Enjoy working at the intersection of engineering and applied research.
Are interested in AI and cybersecurity (experience in machine learning or cybersecurity is a plus but not necessary).