Remote AI Data Engineer for Model Evaluation

mercor; United States; Remote; USD 94,000 - 127,000; Full time

Benefits offered by this job

Health benefits

Job summary

Mercor is hiring a Data Engineer (Coding Agent Experience) to tackle data engineering challenges using frontier AI coding agents. Remote work option available, with compensation tied to task acceptance.

You will build and review ETL pipelines, data warehouses, analytics platforms, and distributed data systems, applying engineering judgment to real-world data problems and model-generated outputs. Collaborate with cross-functional teams to ensure scalable, robust data architectures.

Qualifications

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

Responsibilities

• Use frontier AI coding agents to complete and evaluate complex data engineering tasks.
• Review model-generated implementations for 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.

Skills

Data engineering

ETL pipelines

Distributed data systems

AI coding agents

Data infrastructure evaluation

Job description

Mercor is hiring a Data Engineer (Coding Agent Experience) to tackle data engineering challenges using frontier AI coding agents. Remote work option available, with compensation tied to task acceptance.

You will build and review ETL pipelines, data warehouses, analytics platforms, and distributed data systems, applying engineering judgment to real-world data problems and model-generated outputs. Collaborate with cross-functional teams to ensure scalable, robust data architectures.