Remote Data Engineer for Frontier AI Code Agents

Mercor; Greater London; Remote; GBP 102,000 - 205,000; Part time

Job summary

Mercor partners with a leading AI research lab to support a Frontier Code Agents project focused on evaluating and improving frontier AI coding models through structured technical assessments. You will work on realistic data engineering workflows and model evaluation, addressing bugs, edge cases, and scalability considerations in ETL pipelines and distributed data systems.

The role involves sprint-based work with rapid ramp-up, delivering high-quality, assessable outputs for each task.

Qualifications

• 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.
• Experience operating large-scale data platforms is preferred.

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.
• Compare outputs from multiple frontier models and assess their strengths and weaknesses.
• Apply professional engineering judgment to realistic data engineering scenarios.

Skills

Data engineering

ETL pipelines

Distributed data systems

AI coding agents

Model evaluation

Tools

Cursor

Claude Code

Codex

Windsurf

Gemini CLI

Job description

Mercor partners with a leading AI research lab to support a Frontier Code Agents project focused on evaluating and improving frontier AI coding models through structured technical assessments. You will work on realistic data engineering workflows and model evaluation, addressing bugs, edge cases, and scalability considerations in ETL pipelines and distributed data systems.

The role involves sprint-based work with rapid ramp-up, delivering high-quality, assessable outputs for each task.