| Agentic Data Engineer - Locals to Richmond VA - Primarily remote at Richmond, Virginia, USA |
| Email: [email protected] |
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https://jobs.nvoids.com/job_details.jsp?id=2260959&uid= From: k mahesh, Msys Inc [email protected] Reply to: [email protected] Title:Agentic Data Engineer - Locals to Richmond VA - Primarily remote Location: Richmond, VA, United States Length: Long term Restriction: W2 or C2C Send resumes to : [email protected] Description: ** **Long term*** ***Hybrid*** ** Description: Resource will need to be in Richmond, VA quarterly Agentic Data Engineer to design, develop, and deploy data pipelines that leverage agentic AI that solve real-world problems Job Description: The Virginia Department of Transportations Information Technology Division is seeking a highly skilled Agentic Data Engineer to design, develop, and deploy data pipelines that leverage agentic AI that solve real-world problems. The ideal candidate will have experience in designing data process to support agentic systems, ensure data quality and facilitating interaction between agents and data. Responsibilities: Designing and developing data pipelines for agentic systems, develop Robust data flows to handle complex interactions between AI agents and Data sources. Ability to train and fine tune large language models Design and build the data architecture, including databases, data lakes to support various data engineering tasks. Develop and manage Extract, Load, transform (ELT) processes to ensure data is accurately and efficiently moved from source systems to analytical platforms used in data science. Implement data pipelines that facilitate feedback loops, allowing human input to improve system performance in human-in-the-loop systems. Work with vector databases to store and retrieve embeddings efficiently. Collaborate with data scientists and engineers to preprocess data, train models, and integrate AI into applications. Optimize data storage and retrieval with high performance Statistical analysis, trends, patterns to create data formats from multiple sources. Qualifications: Strong Data engineering fundamentals Utilize Big data frameworks like Spark/Databricks Training LLMs with structed and unstructured data sets. Understanding of Graph DB Experience with Azure Blob Storage, Azure Data Lakes, Azure Databricks Experience implementing Azure Machine Learning, Azure Computer Vision, Azure Video Indexer, Azure OpenAI models, Azure Media Services, Azure AI Search Determine effective data partitioning criteria Utilize data storage system spark to implement partition schemes Understanding core machine learning concepts and algorithms Familiarity with Cloud computing skills Strong programming skills in Python and experience with AI/ML frameworks. Proficiency in vector databases and embedding models for retrieval tasks. Expertise in integrating with AI agent frameworks. Experience with cloud AI services (Azure AI). Experience with GIS spatial data to create markers on maps ( lat long nearest topology of road, geo-locate between datasets, correlation etc.). Experience with Department of Transportation Data Domains developing an AI Composite Agentic Solution designed to identify and analyzedata models, connect & correlateinformation to validatehypotheses, forecast, predict and recommendpotential strategies and conduct What-if analysis. Bachelors or masters degree in computer science, AI, Data Science, or a related field. Required Skills Understanding the Big data Technologies 1 Years Experience developing ETL and ELT pipelines 1 Years Experience with Spark, GraphDB, Azure Databricks 1 Years Expertise in Data Partitioning 1 Years Experience with Data conflation 3 Years Experience developing Python Scripts 3 Years Experience training LLMs with structured and unstructured data sets 2 Years Experience with GIS spatial data 3 Years Keywords: artificial intelligence machine learning database wtwo Virginia Agentic Data Engineer - Locals to Richmond VA - Primarily remote [email protected] https://jobs.nvoids.com/job_details.jsp?id=2260959&uid= |
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| 10:28 PM 17-Mar-25 |