Data Engineer - AI Model Evaluation

mercor; San Francisco (CA); Hybrid; GBP 83,000 - 94,000; Full time

Job summary

Mercor is seeking a Data Engineer (Coding Agent Experience) for a remote, contract role. You will work with frontier AI coding agents to design, implement, and evaluate data infrastructure solutions across ETL pipelines, warehouses, and analytics platforms.

The role emphasizes evaluating model outputs, identifying edge cases, and applying professional engineering judgment in distributed systems. Prior experience with AI coding agents is required.

Qualifications

• 2+ years of professional data engineering experience.
• Experience building ETL pipelines, data warehouses, or distributed data systems.
• Regular use of AI coding agents (Cursor, Claude Code, Codex, Windsurf, Gemini CLI).
• Ability to evaluate model-generated data infrastructure and pipelines.

Responsibilities

• Use frontier AI coding agents to complete and evaluate complex tasks.
• Review model-generated implementations of ETL pipelines, data warehouses, analytics platforms, and distributed data systems.
• Identify bugs, edge cases, scalability issues, and failure modes in model outputs.
• Compare outputs from multiple frontier models and assess strengths and weaknesses.
• Apply professional engineering judgment to realistic data engineering scenarios.

Skills

Data engineering

ETL pipelines

AI coding agents

Model evaluation

Tools

Cursor

Claude Code

Codex

Windsurf

Gemini CLI

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .

Position

Data Engineer (Coding Agent Experience) Type: Contract Compensation: $80/hour Location: Remote

Role Responsibilities

• Use frontier AI coding agents to complete and evaluate complex data engineering tasks.
• Review model-generated implementations involving ETL pipelines , data warehouses , analytics platforms , and distributed data systems .
• Identify bugs, edge cases, scalability issues, and failure modes in model outputs.
• Compare outputs from multiple frontier models and assess their strengths and weaknesses.
• Apply professional engineering judgment to realistic data engineering scenarios.

Qualifications

Must-Have

• 2+ years of professional data engineering experience.
• Experience building ETL pipelines , data warehouses , analytics platforms , or distributed data systems .
• Regular use of AI coding agents such as Cursor , Claude Code , Codex , Windsurf , Gemini CLI , or similar tools.
• Ability to evaluate model-generated data infrastructure and pipeline implementations.

Preferred

• Experience operating large-scale data platforms .

Compensation & Legal

• $400 per accepted task .
• Compensation is tied to accepted work.