Senior Software Engineering Experts

Mercor is working with a leading AI research lab on a project to improve how AI systems do real-world software engineering work. We're looking for senior software engineers who have deep experience at top technology, quantitative or financial firms. You'll use that expertise to train and evaluate frontier AI models. 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

Ideal Profile

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