Remote Research Data Engineer: AI Data Pipelines

TEKsystems; United States; Remote; USD 96,000 - 124,000; Full time

Benefits offered by this job

Medical, dental & vision

401(k) Retirement Plan

Life Insurance

PTO / Vacation

Transportation benefits

Job summary

TEKsystems is seeking a Research Data Engineer in Redmond, WA to support the development of Computer Use Agents and next-generation AI systems. You will work at the intersection of data engineering, analytics, AI research, and vendor operations, helping build and evaluate large-scale training datasets, improve data quality, automate workflows, and develop research tooling for researchers.

The successful candidate thrives in ambiguity, can drive initiatives from investigation through execution,

Qualifications

• Strong Python and SQL programming skills.
• Experience with large-scale data analysis and engineering.
• Strong debugging and problem-solving abilities.
• Experience building automation, tooling, or data pipelines.
• Excellent communication and stakeholder management.
• Ability to work independently in fast-moving, ambiguous environments.

Responsibilities

• Analyze large-scale datasets to identify quality issues and gaps.
• Build scalable pipelines, automation, dashboards, and tooling for AI data generation and evaluation.
• Establish data quality metrics, reporting frameworks, and operational processes.
• Collaborate with external vendors to improve data collection workflows.
• Support research environments, evaluation systems, and experimentation workflows.
• Debug data, tooling, infrastructure, and environment issues.
• Investigate long-tail domains, edge cases, and system failure modes.
• Partner with researchers and engineers to accelerate AI development.

Skills

Python

SQL

CUA

Data Science

Job description

TEKsystems is seeking a Research Data Engineer in Redmond, WA to support the development of Computer Use Agents and next-generation AI systems. You will work at the intersection of data engineering, analytics, AI research, and vendor operations, helping build and evaluate large-scale training datasets, improve data quality, automate workflows, and develop research tooling for researchers.

The successful candidate thrives in ambiguity, can drive initiatives from investigation through execution,