Chief Technology Officer (AI Safety Applied-Research Lab) – Confidential

About Us We are a well-funded AI safety applied-research lab on a mission to make AI agents follow the law in the real world. We are currently in stealth with limited public information, but we have already engaged design partners eager for our technology. We build evaluations that identify AI's legal failure modes, training environments that reduce them, and real-time guardrails that enforce compliance in production — starting with financial services as our first vertical. Founded by Christina Knight — who spent nine years working on AI safety across Stanford, the U.S. government (where she helped start the Center for AI Standards and Innovation), Scale AI, and Harvard Law/MBA — alongside her co-founder, a researcher and postdoc at MIT and Harvard. We have raised $9.2 million in pre-seed funding from 8VC and Floodgate. We are a small, rapidly growing team of engineers, legal experts, and researchers based in San Francisco. Our culture is fast-paced, research-driven, and high-agency — a team of "super-learners, believers, and doers" who embrace uncertainty, ask hard questions, and ship solutions to frontier problems that have no predefined answers.

What You'll Be Doing

• Building legal evaluations (RL environments) to measure AI's failure modes in financial services
• Productionizing the existing research MVP into real-time guardrails for design partners
• Setting technical architecture and research direction alongside the founders
• Hiring and mentoring 3–6 engineers in your first year to build out the engineering team
• Working hands-on with design partners — iterating directly on their needs while building core infrastructure

This is a research-heavy problem with no predefined solution. You will need to be comfortable with uncertainty — not uncertainty in company stability (we have a long runway), but in the nature of the work itself.

Basic Qualifications

• 5–10 years of experience as a CTO, Head of Engineering, or engineering leader
• Proven ability to manage people effectively and build engineering teams
• Strong background in building and deploying AI or LLM products
• Willingness and ability to work on-site in San Francisco, 5 days a week
• Open to visa transfers (e.g., OPT, H1B transfers)

Preferred Qualifications

• Experience with agent systems, RAG, on-prem model deployment, or building evals and testing environments
• Background from fast-paced, high-intensity environments (e.g., Ramp, Mercury, Kalshi, Perplexity)
• CS or technical degree (not a hard requirement — proven ability matters more)
• Quant trading background (often a strong signal of intelligence and resilience)
• Personal interest in AI safety, legal tech, or governance

Tech Stack

Python, TypeScript, AWS, Kubernetes, Docker, Postgres, Prometheus, Grafana, Datadog, Claude Code

Interview Process

• Vibes check / intro call: 20–30 minutes with a founder
• Technical screen: 1 hour, deep engineering assessment
• On-site: 4 hours, including system design and team collaboration

Pay: $250,000.00 - $350,000.00 per year

Application Question(s):

• Are you willing and able to work on-site in San Francisco, CA, 5 days a week?
• This role requires hiring and mentoring 3–6 engineers in the first year. How many engineers have you directly hired and managed in your previous roles?
• We are a 4-person stealth startup. You might work on a critical problem for two weeks, only to pivot based on new priorities. Are you comfortable with this level of ambiguity and rapid change?

Work Location: In person