Research Engineer, AI Security

The Role

Our product is only as good as our agents' judgment. As a Research Engineer on AI Security, you make that judgment better and measurably so: how our agents plan, reason over a graph of a customer's production system, decide what is worth testing, and know when a finding is real.

This sits between research and engineering. In one week you might design an eval that catches a new class of false positive, change how an agent plans a multi-step investigation, compare models on a hard benchmark, and harden the agents themselves against prompt injection from the systems they inspect. You'll work directly with the founders, our engineers, and the security leads who run pentests with our agents, and your work ships to production.

What You'll Do

• Agent reasoning: improve how our agents plan, use tools, and reason over a live graph of code, cloud, and telemetry, so they reach real findings faster and with fewer dead ends.
• Evaluation: build the evals, benchmarks, and graders that tell us whether an agent actually got better, and make them part of how every change ships.
• Model selection and tuning: compare models, prompts, and agent designs on cost, latency, and quality, and turn the results into production decisions.
• Model and agent security: defend our agents against prompt injection, data exfiltration, and manipulation by the very systems they test, and research the security of LLM-based applications our customers build.
• Reliability at scale: make long-running agents dependable across thousands of runs: verification, self-checks, and sensible stopping.
• Learning from the field: study agent runs from customer engagements, find where reasoning broke, and turn each failure into an eval and a fix.

What We're Looking for

• Hands-on experience building, evaluating, or improving LLM-based agents or systems in production.
• A rigorous, empirical approach: you design experiments, distrust single anecdotes, and let the evals decide.
• Strong engineering skills: you write production-quality code (Python, TypeScript, or Go) and build tools other people rely on.
• A working understanding of security, or a strong drive to learn it fast: how real systems are attacked and how findings are validated.
• Familiarity with LLM security risks such as prompt injection, jailbreaks, and tool misuse.
• You build with AI coding agents daily (e.g., Claude Code, Cursor) and have opinions about what makes them reliable.

Nice to Have

• Research background in machine learning, AI safety, or security: publications, open-source work, or talks.
• Offensive security experience: penetration testing, red teaming, bug bounty, or CTFs.
• Experience with reinforcement learning, fine-tuning, or synthetic data generation for agents.
• Experience with graph data models or reasoning over structured data.
• Prior early-stage startup experience.

Compensation & Benefits

• Competitive salary, depending on level and experience.
• Early-stage equity: you're joining early; you'll own a real piece of what we build.
• Comprehensive medical, dental, and vision coverage, and the equipment you need to do your best work.
• Based in San Francisco; we work in person.