AI Data Engineer

About the role

As an IT Specialist (AI Data Engineer) with the US Office of Personnel Management, Office of the Chief Information Officer, Products and Data Engineering Division, you will design, integrate, and modernize enterprise data pipelines, artificial intelligence-enabled data systems, and data architecture solutions that support mission operations, data governance, and technology decision-making. Specialized Experience - GS-13 Applicants must have one year of specialized experience equivalent to at least the GS-12 level in the Federal service, or equivalent, performing data engineering and data architecture work that includes: Developing, testing, implementing, or maintaining data pipelines, feature pipelines, vector or embedding pipelines, or data architecture components supporting artificial intelligence or machine learning systems; Supporting unstructured data ingestion, dataset preparation, data transformation, or data quality monitoring for documents, images, non-tabular sources, or other enterprise data sources; Applying data governance practices, such as metadata management, data lineage, data cataloging, master data management, data quality controls, or shared data asset management; Analyzing data integration, cloud data architecture, system interoperability, platform migration, or build-versus-buy options and preparing technical recommendations for review; and Preparing technical documentation, briefings, post-incident findings, or implementation guidance for technical staff, program officials, customers, or management. Specialized Experience - GS-14 Applicants must have one year of specialized experience equivalent to at least the GS-13 level in the Federal service, or equivalent, performing data engineering and data architecture work that includes: Designing, implementing, or modernizing data pipelines, feature pipelines, vector or embedding pipelines, or data architecture solutions supporting artificial intelligence or machine learning systems; Developing technical approaches for unstructured data ingestion, model-ready dataset preparation, production telemetry, model drift detection, data quality monitoring, or operational observability; Developing or recommending data governance controls, standards, or implementation guidance for metadata management, data lineage, data cataloging, master data management, data quality, or shared data assets; Evaluating data integration patterns, application programming interfaces, cloud data architecture, platform migration, tool selection, or build-versus-buy options and recommending technical approaches to management; and Communicating technical requirements, risks, findings, recommendations, or implementation options through architecture documents, briefings, post-incident reviews, or stakeholder discussions. You must meet all qualification and eligibility requirements by the closing date of this announcement. Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic; religious; spiritual; community, student, social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.

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Company Intel

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