Oath Technologies - Research Engineer, Tools & Infrastructure

Convergent Research•Berkeley, CA

1d•$250,000 - $385,000•Onsite

About The Position

Oath Technologies is a new research organization building tools for oversight of advanced AIs. As AIs become more powerful, it will become more difficult to understand and monitor their behavior. Oath is building oversight tools based on formal verification: rather than monitor AIs directly, humans define unambiguous rules, and AIs must provide trustworthy mathematical evidence of compliance. In this way, Oath will help keep humans safe and in control as AI advances. Oath is a Focused Research Organization (FRO) incubated and fiscally sponsored by Convergent Research. Convergent has incubated 12 FROs spanning mathematics, astrophysics, neuroscience, climate, biology, and AI, including the Lean FRO (formal mathematics and verification) and E11 Bio (whole-brain circuit mapping). Oath is led by CEO Dr. Mike Dodds, and is based in Berkeley, CA. Oath's research engineers will build novel formal methods tools and apply them at scale to AI oversight problems. To do this, we are hiring both formal methods specialists and engineers with skills such as developer tools, scalable testing, agent development, AI/ML, and others that complement Oath's mission. Engineers may have skills in one or several areas, and our team will be tightly integrated, with both categories working together. Oath will target very difficult verification and oversight problems, far beyond previous formal verification projects in scale and complexity. Oath's research team will work iteratively, building tools, testing them on our flagship problems, identifying failures, and then feeding those back into our tool designs. We plan to build an Oath team of around six people by the end of year one, growing to a steady state of around twelve people by year three. Oath's roadmap runs for five years, and we’ll set more ambitious targets as the outcomes of our work and changes in the profile of AI risk evolve. This is a strong fit for people who want to tackle complex, high-stakes challenges in a nimble, collaborative organization. Oath's current plan is to build tools across three families: design (authoring new specifications), lifting (extracting specifications from existing systems that have none), and audit (stress-testing specifications for gaps or adversarial manipulation). We're applying these to a first flagship target, verified agent containment: proving that an AI agent can't escape the permissions and sandboxing meant to bound it, from the OCI container runtime down to Linux kernel isolation primitives. Most of this work will be done in Lean or adjacent formal-verification infrastructure, with AI agents doing much of the day-to-day drafting and proving under close review.

Requirements

Experience building tools engineers actually adopt: IDE integrations, language servers, CLI tooling, build-system integration.
Experience with AI-assisted developer workflows, agent scaffolding, or applied AI/ML engineering.
Comfort picking up formal methods concepts on the job, even without prior depth in the area.
Experience working in research and/or engineering teams delivering ambitious results.
An ability to learn quickly, build quickly, and pivot when necessary.

Nice To Haves

Experience using coding agents or other AI tools for ambitious technical projects.
Knowledge of AI risks generally, and alignment with Oath's mission to counter AI risks.
A broad enthusiasm for deeply technical topics, and a passion for ideas.

Responsibilities

Contribute directly to Oath's research goals: building tools, applying them to real systems, and iterating based on what works.
Help scale Oath's tools to large, long-running experiments intended to map the frontiers of AI oversight capabilities.
Take deep ownership of problems, from framing the question, to overcoming obstacles, to delivering a working solution.
Collaborate closely with a small, high-context team, including significant use of AI agents as part of the day-to-day workflow.
Help set technical direction as the team and its workstreams grow, not just execute someone else's plan.
Document your work and reasoning so it doesn't stay trapped in one person's head.