AI Engineer (Offensive Security)

You're a strong engineer who's gone deep on LLMs and agents. You write good quality code, you think rigorously, you take problems and run with them end to end.

What experience you need to be successful

• Strong production engineering experience
• You should have proven experience writing high-quality production code and building reliable applications across at least a portion of our tech stack. This includes writing testable and maintainable software, designing systems end to end, working with CI/CD, deploying services, debugging production issues, and making sensible engineering trade-offs.
• Experience building and evaluating agentic workflows
• You must have hands-on experience building agentic workflows or LLM-based systems that involve tool use, multi-step reasoning, orchestration, evaluation, or automation.
• We are especially interested in people who have thought deeply about how agents fail, how to measure performance, and how to move beyond impressive demos into reliable systems. This experience may come from professional work, open-source contributions, research, or serious side projects.
• Ownership, judgement, and clear communication.
• You’re excited to work on a frontier problem where AI is being applied to real offensive security workflows in new and meaningful ways. You can take a rough idea, shape the approach, make good technical decisions, build and ship the system, and iterate based on feedback. You keep the wider goal in view, test assumptions quickly, adapt as we learn, and communicate clearly throughout, whether you’re documenting an architecture decision or explaining an agent failure mode to a non-AI specialist.
• Docker and AWS. You don’t need deep experience in all of these
• but you should be comfortable building production-quality systems and learning quickly.
• Most of the work sits at the intersection of engineering
• and usable internal tooling.