What the work is
This role is open to candidates based in the United States, United Kingdom, Canada, Australia or New Zealand.
Key Responsibilities
- Designing realistic, challenging software engineering tasks drawn from real-world work, including but not limited to:
- feature changes in large codebases
- debugging and root-cause analysis
- code review
- system design and architecture decisions
- codebase Q&A
- technical documentation and planning
- Writing clear task proposals that explain why each task is realistic, how it is verified and what makes it hard for current AI models
- Illustrating "what good looks like" by writing reference solutions, tests and precise, task-specific criteria covering correctness, architecture, maintainability, style and scope
- Assessing AI-generated code and engineering work, and working alongside AI coding agents to judge where they succeed and fail
- Applying consistent, evidence-based judgment so that assessments are reproducible and defensible
- Taking structured feedback from senior reviewers and iterating on submitted work
Who gets hired
- 4+ years of professional software engineering experience in one of these settings:
- A leading technology or quantitative firm (such as FAANG+, Magnificent 7+, top-tier quant funds or equivalent) with a Mid-senior level title. Machine Learning, Infrastructure, Data, Security and Quant Developer engineering roles may also qualify.
- A top financial institution (a leading bank, hedge fund or trading firm), working as a software engineer
- A high-growth technology company that is a household name, with a senior-level title
- Experience may be split across more than one qualifying employer
- Strong command of at least one major language (such as Python, Java, C++, Go, TypeScript or Rust), along with system design, testing, debugging and code review
- Proven ability to work in large, complex production codebases and to judge code quality beyond "it passes the tests"
- Excellent written English, including the ability to explain technical decisions and trade-offs clearly
- Bachelor's degree from an English-speaking country
- A detail-oriented, consistent approach to evaluating complex work
- Comfortable receiving feedback and calibrating judgment against set standards
The platform posted this on 27 Oct 2026.