We're partnering with an AI safety applied-research lab focused on ensuring AI agents follow the law in real-world deployments. The company is building evaluations, training environments, and runtime guardrails that help AI systems understand and comply with legal and regulatory requirements.Its initial focus is financial services, where AI agents increasingly interact with highly regulated workflows and real-world systems.
Company Snapshot
- $9.2M pre-seed funding, backed by 8VC and Floodgate.
- Founded in 2025 and currently operating in stealth.
- Led by founders with backgrounds spanning Stanford, MIT, Harvard, Scale AI, and the US government.
- Elite, high-agency team of engineers, legal experts, and researchers.
- Building across three core areas: legal evaluations, training environments, and real-time runtime guardrails.
- Starting with financial services as the first vertical, with design partners already engaged.
About the Role
As a Founding Research Engineer, you'll advance research on law-following AI across evaluations, training, and runtime control. You'll design experiments, build evaluation environments and training pipelines, develop methods for validating LLM judges, and work closely with legal experts to ground the research in real-world legal practice. You'll own projects end to end, from research design through implementation, experimentation, and publication.
Why You Should Join
- Take a founding research seat at the intersection of AI safety, machine learning, and law.
- Own research projects from initial hypothesis through experimentation and publication.
- Work directly with founders, research leadership, lawyers, and an academic advisory board.
- Build evaluations and training environments for frontier AI agents.
- Work on an emerging AI safety problem with no established playbook.
- Have meaningful influence over the research direction, product, and technical architecture.
- Join a highly technical, research-driven team operating with significant ownership and speed.
Qualifications
- 1–5 years of experience in applied research, ML engineering, or a closely related field.
- Degree in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
- Experience in AI safety, alignment, evaluations, or related research, through industry work, academia, publications, or open-source projects.
- Strong engineering skills in Python and the modern ML stack.
- Strong ability to tackle ambiguous research problems without predefined solutions.
- Experience building or working with evaluations, training environments, post-training pipelines, or AI agents is highly relevant.
- Comfortable working in a fast-paced startup environment while maintaining strong research rigor.
- Legal training or research in law and computation is a plus.
- Experience training or validating LLM judges is a plus.
Pay range and compensation package
- Compensation: $185K–$350K + Competitive Equity