Senior Software Engineer

Weekday AI

5d•$30 - $100•Remote

About The Position

This contractor role supports a client’s training and evaluation of next-generation artificial intelligence systems. The Senior Software Engineer designs realistic, challenging coding tasks that assess feature implementation, bug fixing, code refactoring, and performance optimization. The role also involves developing reference solutions and deterministic verification mechanisms that validate submissions against defined requirements and accept reasonable correct implementations while rejecting incorrect or incomplete ones. The work draws on backend engineering expertise, debugging experience, software testing knowledge, and independent technical judgment. Responsibilities include creating tasks and evaluation criteria, developing test suites and verification scripts, assessing AI-generated code and reasoning, and refining evaluation methods based on model failures. Previous AI experience is not required. The position is remote, approximately 15 hours per week, with a flexible schedule. Compensation is listed at $30–$100 per hour and is output-based: payment is provided for tasks that meet project specifications and acceptance criteria. Minimum weekly task submission requirements apply. Candidates should be prepared to start their first tasks within 24–48 hours after onboarding.

Requirements

Strong professional software engineering experience, particularly in backend development and production-grade systems.
Proficiency in one or more programming languages, including Java, Node.js, Go, Rust, TypeScript, Python, C++, or similar technologies.
Proven experience designing, building, and maintaining scalable services and APIs.
Strong understanding of data structures, algorithms, system design, and fundamental computer science concepts.
Extensive experience with debugging, troubleshooting, performance optimization, and code review.
Practical experience with automated testing, test design, and software quality assurance.
Ability to identify implementation defects, edge cases, inefficient algorithms, and architectural weaknesses.
Strong understanding of code maintainability, refactoring, reliability, and software engineering best practices.
Excellent analytical, problem-solving, and technical communication skills.
Ability to work independently and exercise sound technical judgment when evaluating complex engineering problems.
Complete interviews and assessments independently, without assistance from AI tools or other individuals.
Meet the specified minimum number of task submissions per week.

Nice To Haves

Experience designing and maintaining large-scale test suites.
Experience diagnosing and resolving flaky tests.
Experience with test automation frameworks.
Experience with continuous integration and continuous delivery (CI/CD).
Knowledge of distributed systems and microservices.
Knowledge of system architecture and design patterns.
Experience with regression, integration, and unit testing.
Experience with deterministic evaluation and automated verification.
Experience evaluating AI coding agents.
Experience modernizing legacy systems.
Experience in production reliability and performance engineering.
Demonstrated success delivering scalable, reliable, high-performance backend applications.
Experience resolving complex software defects and improving system performance.
Proven ability to implement complex features and refactor large codebases.
Strong background in test strategy, automated validation, and improving engineering quality standards.
Experience establishing testing best practices across engineering teams.
Ability to translate complex engineering requirements into clear, reproducible coding tasks and evaluation criteria.

Responsibilities

Design challenging, realistic coding tasks involving feature implementation, bug fixes, refactoring, and performance optimization.
Create high-quality reference implementations that demonstrate correct, efficient, and maintainable solutions.
Build deterministic verifiers, validation scripts, and comprehensive test cases to assess solution correctness.
Apply backend engineering knowledge of scalable services, APIs, asynchronous processing, and distributed systems to create realistic engineering challenges.
Debug complex defects, investigate system bottlenecks, and identify root causes of unexpected behavior.
Design testing strategies, maintain large test suites, diagnose flaky tests, and improve software quality.
Review code for correctness, readability, maintainability, performance, security, and alignment with engineering best practices.
Develop tasks that assess refactoring legacy code, simplifying complex implementations, and optimizing resource use.
Evaluate AI-generated reasoning related to architecture, debugging, algorithms, system design, and implementation decisions.
Document task requirements, expected behavior, test coverage, solution approaches, and verification criteria.
Analyze model failures and refine coding tasks and evaluation methods to improve the quality and reliability of AI-generated software.