{"schemaVersion":"jobsearcher.job.v1","id":"b2c54c418c1abdede4c1bd9e","url":"https://jobsearcher.com/jobs/b2c54c418c1abdede4c1bd9e","canonicalUrl":"https://jobsearcher.com/jobs/b2c54c418c1abdede4c1bd9e","title":"Agentic Engineer.","description":"Interview Mode: Either Phone or In Person\nThe client is seeking a highly skilled Agentic Engineer to design, develop 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.\nResponsibilities Design and develop data pipelines for agentic systems; develop robust data flows to handle complex interactions between AI agents and data sources.\nTrain and fine-tune large language models (LLMs).\nDesign and build data architecture, including databases and data lakes, to support various data engineering tasks.\nDevelop 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.\nImplement data pipelines that facilitate feedback loops, allowing human input to improve system performance in human-in-the-loop systems.\nWork with vector databases to store and retrieve embeddings efficiently.\nCollaborate with data scientists and engineers to preprocess data, train models, and integrate AI into applications.\nOptimize data storage and retrieval for high performance.\nConduct statistical analysis to identify trends and patterns and create data formats from multiple sources.\nQualifications Strong data engineering fundamentals.\nExperience with big data frameworks such as Apache Spark and Azure Databricks.\nAbility to train LLMs using structured and unstructured datasets.\nUnderstanding of graph databases.\nExperience with Azure services including Blob Storage, Data Lakes, Databricks, Azure Machine Learning, Azure Computer Vision, Azure Video Indexer, Azure OpenAI, Azure Media Services, and Azure AI Search.\nProficient in determining effective data partitioning criteria and implementing partition schemas using Spark.\nUnderstanding of core machine learning concepts and algorithms.\nFamiliarity with cloud computing concepts and practices.\nStrong programming skills in Python and experience with AI/ML frameworks.\nProficiency in working with vector databases and embedding models for retrieval tasks.\nExpertise in integrating with AI agent frameworks.\nExperience with cloud-based AI services, especially Azure AI.\nProficient with version control systems such as Git.\nBachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.\nAdditional Experience Requirements Understanding the Big data technologies — Required — 5 Years\nExperience developing ETL and ELT pipelines — Required — 5 Years\nExperience with Spark, GraphDB, Azure Databricks — Required — 5 Years\nExperience training LLMs with structured and unstructured data sets — Required — 4 Years\nExperience in Data Partitioning and Data conflation — Required — 3 Years\nExperience with GIS spatial data — Required — 3 Years\n\n#J-18808-Ljbffr","company":"Beyond Sof","rawCompany":"beyond sof","city":"Henrico","state":"VA","isRemote":false,"isActive":false,"createdAt":"2026-06-17T04:17:11.780Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Agentic Engineer.","description":"Interview Mode: Either Phone or In Person\nThe client is seeking a highly skilled Agentic Engineer to design, develop 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.\nResponsibilities Design and develop data pipelines for agentic systems; develop robust data flows to handle complex interactions between AI agents and data sources.\nTrain and fine-tune large language models (LLMs).\nDesign and build data architecture, including databases and data lakes, to support various data engineering tasks.\nDevelop 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.\nImplement data pipelines that facilitate feedback loops, allowing human input to improve system performance in human-in-the-loop systems.\nWork with vector databases to store and retrieve embeddings efficiently.\nCollaborate with data scientists and engineers to preprocess data, train models, and integrate AI into applications.\nOptimize data storage and retrieval for high performance.\nConduct statistical analysis to identify trends and patterns and create data formats from multiple sources.\nQualifications Strong data engineering fundamentals.\nExperience with big data frameworks such as Apache Spark and Azure Databricks.\nAbility to train LLMs using structured and unstructured datasets.\nUnderstanding of graph databases.\nExperience with Azure services including Blob Storage, Data Lakes, Databricks, Azure Machine Learning, Azure Computer Vision, Azure Video Indexer, Azure OpenAI, Azure Media Services, and Azure AI Search.\nProficient in determining effective data partitioning criteria and implementing partition schemas using Spark.\nUnderstanding of core machine learning concepts and algorithms.\nFamiliarity with cloud computing concepts and practices.\nStrong programming skills in Python and experience with AI/ML frameworks.\nProficiency in working with vector databases and embedding models for retrieval tasks.\nExpertise in integrating with AI agent frameworks.\nExperience with cloud-based AI services, especially Azure AI.\nProficient with version control systems such as Git.\nBachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.\nAdditional Experience Requirements Understanding the Big data technologies — Required — 5 Years\nExperience developing ETL and ELT pipelines — Required — 5 Years\nExperience with Spark, GraphDB, Azure Databricks — Required — 5 Years\nExperience training LLMs with structured and unstructured data sets — Required — 4 Years\nExperience in Data Partitioning and Data conflation — Required — 3 Years\nExperience with GIS spatial data — Required — 3 Years\n\n#J-18808-Ljbffr","datePosted":"2026-06-17T04:17:11.780Z","dateModified":"2026-06-17T04:17:11.780Z","hiringOrganization":{"@type":"Organization","name":"Beyond Sof","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Henrico","addressRegion":"VA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"b2c54c418c1abdede4c1bd9e"},"url":"https://jobsearcher.com/jobs/b2c54c418c1abdede4c1bd9e"}}