System Soft Technologies

Sr. Data Engineer - AI

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr. Data Engineer - AI in Seattle, WA, with a contract length of "unknown" and a pay rate of "unknown." Requires 10+ years in data engineering, expertise in cloud platforms, and familiarity with AI/ML data pipelines.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
June 19, 2026
πŸ•’ - Duration
Unknown
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🏝️ - Location
On-site
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Seattle, WA
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🧠 - Skills detailed
#Compliance #AWS (Amazon Web Services) #Data Management #Data Ingestion #Batch #Data Pipeline #Knowledge Graph #Metadata #Data Architecture #GCP (Google Cloud Platform) #Data Governance #Data Engineering #Security #ML (Machine Learning) #Azure #Datasets #Cloud #Scala #Databases #AI (Artificial Intelligence) #Data Quality #"ETL (Extract #Transform #Load)"
Role description
Sr. Data Engineer - AI Location: Seattle WA Role Summary We are seeking a senior Data Engineer to design and build enterprise-scale data platforms that enable AI/ML and agentic systems. This role focuses on engineering AI-ready data foundationsβ€”ensuring data is high-quality, governed, and optimized for advanced analytics and autonomous AI agents. Sr. Data Engineer - AI-ready-Enterprise-Scale Data Platforms Key Responsibilities β€’ Architect and build scalable, cloud-native data platforms supporting AI/ML and agent-based applications β€’ Design pipelines to deliver AI-ready data (curated, labeled, contextualized, and feature-rich datasets) β€’ Develop robust data ingestion, transformation, and serving layers (batch + real-time) β€’ Enable semantic data models, knowledge graphs, and vector databases to power AI agents and LLMs β€’ Implement data quality, lineage, and governance frameworks to ensure trust and compliance β€’ Collaborate with AI/ML teams to support feature engineering, model training, and inference pipelines β€’ Optimize data architectures for performance, scalability, and cost efficiency β€’ Mentor teams and establish best practices for AI-driven data engineering Required Skills & Experience β€’ 10+ years of experience in data engineering and platform architecture β€’ Strong expertise in cloud platforms (Azure, AWS, or GCP) and modern data ecosystems β€’ Familiarity with AI/ML data pipelines, feature stores, and model lifecycle support β€’ Experience with LLM data pipelines β€’ Strong understanding of data governance, metadata management, and security frameworks Preferred Qualifications β€’ Experience building data platforms for AI agents / agentic workflows β€’ Knowledge of RAG (Retrieval Augmented Generation) architectures and semantic search β€’ Exposure to data mesh / domain-oriented data architectures β€’ Experience in large-scale enterprise transformation programs