AI Data Engineer

About the Role

This is a remote, contract-based opportunity in the United States for an AI Data Engineer. The role involves building and optimizing data infrastructure for intelligent products and AI-enabled applications.

Key Responsibilities

• AI Data Pipeline Development: Design, build, and maintain scalable data pipelines that support AI workloads, intelligent products, and data-intensive applications.
• Synthetic Data Generation: Develop and maintain automated workflows for generating synthetic data to support AI development, testing, validation, and product improvement.
• Data Preparation & Processing: Build reliable processes for collecting, transforming, structuring, and preparing large-scale datasets for use in AI-enabled applications.
• Data Modeling & Architecture: Design data models and storage solutions that support efficient data organization, scalability, accessibility, and long-term maintainability.
• Data Validation & Quality Assurance: Implement automated validation processes, quality controls, and monitoring mechanisms to ensure data accuracy, consistency, completeness, and reliability.
• Storage & Retrieval Systems: Develop and optimize backend data systems and retrieval mechanisms that enable efficient access to relevant information for AI applications and intelligent products.
• Scalable Backend Engineering: Build and maintain robust data infrastructure capable of handling large datasets, evolving workloads, and changing application requirements.
• AI Product Integration: Collaborate with product managers, software engineers, and AI development teams to align data infrastructure with application requirements and product objectives.
• Workflow Automation: Identify opportunities to automate repetitive data engineering tasks, improve processing efficiency, and reduce manual intervention across data workflows.
• Performance Optimization & Troubleshooting: Investigate data pipeline failures, storage limitations, and retrieval bottlenecks, implementing improvements that strengthen system performance and reliability.
• Continuous Improvement: Evaluate data engineering practices and emerging approaches to improve scalability, maintainability, and the effectiveness of AI data infrastructure.

Requirements & Tech Stack

• Python Proficiency: Strong programming skills in Python for data processing, workflow automation, pipeline development, and backend data engineering.
• AI Data Engineering Experience: Practical experience designing, developing, or maintaining scalable data pipelines for AI workloads, intelligent products, or other data-intensive applications.
• Data Generation & Preparation: Experience developing automated data generation, data transformation, or data preparation workflows.
• Data Modeling & Storage: Demonstrated ability to design data models and storage solutions for large-scale datasets.
• Data Validation & Quality Controls: Experience implementing automated validation, data quality checks, and monitoring processes.
• Backend Data Systems: Ability to develop dependable backend data infrastructure and retrieval mechanisms.
• Scalability & Performance: Understanding of scalable data architecture, efficient processing techniques, and approaches to optimizing data workflows and system performance.
• AI Application Integration: Experience collaborating with product or engineering teams to support the data requirements of AI-driven applications and intelligent products.
• Problem-Solving Skills: Strong analytical thinking and troubleshooting abilities.
• Communication & Collaboration: Ability to work effectively across multidisciplinary teams.
• Remote Work Readiness: Ability to work independently in a remote environment and manage priorities effectively.
• Preferred Experience: Familiarity with Microsoft 365 Copilot or similar enterprise AI products is an advantage.

Qualifications

• This is a contract opportunity based remotely in the United States.
• Applicants should be prepared to provide their current location, work authorization details, desired hourly rate, and current contract end date.
• Competitive Hourly Rate: Indicative compensation ranging from $67 to $77 per hour.
• Employment Type: Contract.
• Experience Level: Entry-level listing, with practical experience in scalable data engineering and AI-related data workflows required.