Senior Python Engineer - AI Code Evaluation
New
J
JobgetherAI Engineering
Based in the United StatesContractSenior
Salary100 - 200 USD per hour
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Job Details
- Required Skills
- PythonJavascriptTypeScript
Requirements
- Staff, Principal, or similarly experienced software engineering background.
- Deep hands-on experience with Python and/or TypeScript/JavaScript.
- Practical experience using AI-assisted development tools such as OpenAI Codex, Claude Code, Cursor, or comparable coding agents.
- Strong familiarity with contemporary AI-assisted software-development workflows.
- Ability to recognize whether an AI response reflects strong engineering thinking, including useful explanations, sound trade-offs, appropriate guidance, and trustworthy recommendations.
- Comfortable evaluating code and technical reasoning at a high level without needing to execute or inspect every implementation detail.
- Ability to provide concise, direct, and opinionated feedback.
- Strong personal standards for effective, maintainable, and professional engineering.
- Exposure to AI-first IDEs, prompt design, or model evaluation workflows is a plus.
- Experience mentoring senior engineers or helping establish engineering standards is beneficial.
Responsibilities
- Review AI-generated coding sessions end to end and assess whether responses are useful, correct at a high level, and aligned with how an experienced engineer would approach the problem.
- Evaluate whether AI agents demonstrate sound reasoning, appropriate trade-offs, clear decision-making, and practical software-engineering judgment rather than simply producing syntactically correct code.
- Judge the quality of model preambles, explanations, reasoning, and guidance, identifying whether they genuinely help developers or simply generate technically accurate but unhelpful output.
- Provide structured feedback by clearly and directly explaining what worked, what did not, and what felt misleading, ineffective, or inconsistent with strong engineering practice.
- Apply consistent standards to distinguish varying levels of AI performance and articulate what separates an average response from an excellent one.
- Contribute to the evolving understanding of what high-quality AI-assisted software development should look like, including interactions with AI-first development environments.
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