Senior Data Engineer – AI Platforms

About the job About The Role Job Title: Data engineer for AI Ready data platforms United States Client – will share later Visa any Needs to work in PST time zone – remote is ok Rate -$75-85/hr- flexible for rock star 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 foundations—ensuring data is high-quality, governed, and optimized for advanced analytics and autonomous AI agents. Key Responsibilities Architect and build scalable, cloud-native data platforms supporting AI/ML and agent-based applications Design pipelines to deliver AI-ready data (curated, labeled, contextualized, and feature-rich datasets) Develop robust data ingestion, transformation, and serving layers (batch + real-time) Enable semantic data models, knowledge graphs, and vector databases to power AI agents and LLMs Implement data quality, lineage, and governance frameworks to ensure trust and compliance Collaborate with AI/ML teams to support feature engineering, model training, and inference pipelines Optimize data architectures for performance, scalability, and cost efficiency Mentor teams and establish best practices for AI-driven data engineering Required Skills & Experience 10+ years of experience in data engineering and platform architecture Strong expertise in cloud platforms (Azure, AWS, or GCP) and modern data ecosystems Familiarity with AI/ML data pipelines, feature stores, and model lifecycle support Experience with LLM data pipelines Strong understanding of data governance, metadata management, and security frameworks Preferred Qualifications Experience building data platforms for AI agents / agentic workflows Knowledge of RAG (Retrieval Augmented Generation) architectures and semantic search Exposure to data mesh / domain-oriented data architectures Experience in large-scale enterprise transformation programs Key Responsibilities & Skills Enterprise-Scale Data Platform Architecture AI/ML Data Pipeline Design AI-Ready Data Curation & Feature Engineering Real-Time & Batch Data Processing Semantic Data Modeling & Knowledge Graphs Vector Database & Retrieval Augmented Generation (RAG) Data Governance, Metadata Management & Lineage Security & Compliance Frameworks for Data Cloud-Native Engineering (Azure / AWS / GCP) Cost & Performance Optimization Mentoring & Best Practices for AI-Driven Data Engineering Data Mesh & Domain-Oriented Architecture Technical Skills Azure / AWS / GCP Python / Scala / Java Spark / Flink / Databricks Airflow / Dagster / Prefect Kafka / Kinesis Snowflake / Redshift / BigQuery Feature Store (Feast) Vector DB (Pinecone / Weaviate / Milvus) Knowledge Graph (Neo4j / RDF) Terraform (IaC) Docker / Kubernetes CI/CD (GitHub Actions / Azure DevOps) Data Catalog (Collibra / Alation) Monitoring (Datadog / Prometheus) Education Bachelor's Degree in Computer Science, Software Engineering, Data Engineering, Information Systems, Computer Engineering, Mathematics. Preferred: Master's in Data Science, Master's in Computer Science, Master's in AI/ML, PhD in Computer Science, PhD in AI, MBA (Technology Management). Industry Experience Technology / AI Cloud Services Enterprise Data Platforms AI/ML & LLM Projects Large-Scale Data Transformation Data Governance & Compliance #JoinOurTeam #NowHiring #ApplyToday Desired Skills and Experience CI/CD (GitHub Actions / Azure DevOps), Metadata Management & Lineage, Knowledge Graph (Neo4j / RDF), Monitoring (Datadog / Prometheus), Data Catalog (Collibra / Alation), Kafka / Kinesis, Azure / AWS / GCP, Vector DB (Pinecone / Weaviate / Milvus), Snowflake / Redshift / BigQuery, Cloud-Native Engineering (Azure / AWS / GCP), Feature Store (Feast), Semantic Data Modeling & Knowledge Graphs, AI/ML Data Pipeline Design, Docker / Kubernetes, Spark / Flink / Databricks, Airflow / Dagster / Prefect, Data Governance, Python / Scala / Java, Terraform (IaC), Enterprise-Scale Data Platform Architecture