Position Overview:

Agentic Data Engineer to design, develop, and deploy data pipelines that leverage agentic AI that solve real-world problems. Our client's 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.

Role : Agentic Data Engineer Location : Richmond, VA (Hybrid) Need candidate within 2hrs drivable distance

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 structured 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, connectcorrelateinformation to validatehypotheses, forecast, predict and recommendpotential strategies and conduct What-if analysis.
Bachelor's or master's degree in computer science, AI, Data Science, or a related field.

Skill

Required / Desired

Amount

Experience

Understanding the Big data Technologies

Required

Years

Experience developing ETL and ELT pipelines

Required

Years

Experience with Spark, GraphDB, Azure Databricks

Required

Years

Expertise in Data Partitioning

Required

Years

Experience with Data conflation

Required

Years

Experience developing Python Scripts

Required

Years

Experience training LLMs with structured and unstructured data sets

Required

Years

Experience with GIS spatial data

Required

Years

JR Software Solutions

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