Staff Software Engineer, UnlikelyAI

• This is a role for someone who combines deep hands-on engineering ability with the judgement and influence to drive architecture and engineering quality across teams
• ...you have deep expertise in Python, including writing well-typed, well-tested code in a collaborative codebase, and strong opinions on how to structure Python projects at scale
• ...you have a proven track record in system design and architecture – you've made foundational technical decisions that shaped the trajectory of a product or platform
• ...you've tackled complex algorithms and data structures and have experience working with non-trivial algorithmic problems at scale
• ...you care deeply about production-quality engineering – you don't just advocate for software quality, you actively set the standards and build the culture around it
• ...you have a track record of technical leadership – you've influenced technical direction across multiple teams or projects without necessarily having direct reports
• ...you have significant experience with cloud infrastructure (AWS preferred) – services such as S3, ECR, ECS/EKS, and infrastructure managed via Terraform or similar – and can make informed architectural decisions about deployment and scalability
• ...you have a bias for action – you move quickly, make informed decisions, and iterate without waiting for perfect information
• ...you have a relevant degree in Computer Science, Mathematics, Engineering, or STEM – or equivalent practical experience

Desirable

• We are looking for a Staff Software Engineer to help shape the technical direction of our platform as we scale
• You'll be one of our most experienced individual contributors – someone the team looks to for guidance on hard technical decisions, system design, and long-term technical strategy
• You'll spend most of your time writing code and solving complex problems, but you'll also be expected to identify the highest-leverage work across squads, mentor other engineers, and raise the bar for how we build software
• Our core capabilities span symbolic reasoning (decision trees, propositional graphs, knowledge graphs), document ingestion pipelines, and the APIs that expose these to customers
• You'll work on genuinely novel problems at the intersection of classical symbolic AI and modern LLMs – for example, how to represent regulatory knowledge as machine-evaluable rules, or how to build feedback loops that improve system accuracy over time
• You'll work within a shared monorepo alongside software engineers, research engineers, and applied scientists in a heavily cross-functional environment
• We operate in small, focused product teams, supported by shared infrastructure, internal tooling, and an R&D function
• In your first months, you could find yourself working on any of the following:
• Defining the architecture for our new public API – making foundational decisions about authentication, scalability, versioning, and developer experience that will shape the platform for years
• Leading the design and implementation of our document ingestion pipelines to handle new input formats (e.g. PDF, Word) and new regulatory jurisdictions at scale
• Designing evaluation frameworks and benchmarks to measure and improve system accuracy – and establishing these as engineering norms across teams
• Driving improvements to our deployment architecture for enterprise customers with specific cloud and security requirements
• Owning the technical strategy for internal tooling and developer experience across the monorepo – identifying bottlenecks and leading initiatives to address them
• Working on the symbolic reasoning engine that powers our products – including decision tree evaluation, rule generation, and knowledge graph construction
• Identifying and leading cross-cutting technical initiatives that improve reliability, performance, or engineering velocity across the organisation

• Intro with Talent
• Optional call with Hiring Manager
• Take-home Challenge
• Full Loop Interview - System Design + Values
• Decision