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Reasonable AI

Applied AI research for formal verification

Founding Forward Deployed Engineer

AI Application EngineeringUpdated on Nov 10
Full-time

About the Job

Requirements

  • Time spent inside or close to a high-accountability engineering culture, with an understanding of the value of correctness and verification.
  • Familiarity with systems languages such as Rust, JVM languages such as Java or Kotlin, or cloud-native languages such as Go.
  • Domain expertise in formal methods or verification, through research or practical application.
  • Understanding of specification-aware programming, including Verus, Dafny, or Viper, and proof assistants and verification tools, including TLA+, Lean, Roq, or Isabelle.
  • Experience building relationships with senior engineers and CTOs.
  • Genuine interest in the commercial side of the work.
  • Comfort working in an early-stage environment with ambiguity, hands-on problem solving, and rapid iteration while producing high-quality output.

Responsibilities

  • Lead discovery by joining early customer meetings, owning technical scoping, and bringing research depth to prospective partner conversations.
  • Diagnose which prospective partners’ systems are suitable for verification and proof-of-concept work, ensuring that proofs of concept solve real and replicable problems.
  • Design proofs of concept and initial customer solutions, translating observations and requirements into tightly scoped deployments that a small team can deliver rapidly.
  • Identify capability gaps that recur across partners and feed those signals directly into research and development priorities, including what to train for and build.
  • Elicit real specifications from complex systems and engineering teams, build trust, and translate between prospective partners and the frontier of AI and formal verification.
  • Remain hands-on between partner conversations as a technical team member, building alongside the wider team.

Desired Qualifications

  • Actively contribute to formal verification or program synthesis projects, such as Verus, Lean, or Dafny.
  • Have run production back-end services at scale and experienced the limitations of testing.
  • Have been accountable for distributed systems and understand failure modes involving concurrency, consensus, and partial failure.

About the Company

Reasonable AI

Applied AI research for formal verification

Reasonable AI builds AI systems for formal verification of mission-critical software. It blends language models with formal methods to generate, repair, and verify machine-checkable proofs that accompany code, using Verus. They train small, specialized models that can match larger systems in proof accuracy while running faster, and analyze how models fail to prevent cheating. Their goal is to reduce the verification bottleneck from AI-assisted code, enabling engineers to produce software with formal correctness guarantees and machine-checkable proofs for each production line.

Company size
1-10
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
2025

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