Job Description

Job Title: Agentic Data Engineer (Hybrid)
Location: Richmond, VA
Duration: 12+ Months

Job Description:
Agentic Data Engineer to design, develop, and deploy data pipelines that leverage agentic AI that solve real-world problems

The client 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 analyze data models, connect & correlate information to validate hypotheses, forecast, predict and recommend potential strategies and conduct What-if analysis.  
• Bachelor's or master's degree in computer science, AI, Data Science, or a related field.

Skills:

 

Skill	Required / Desired	Amount	of Experience
Understanding the Big data Technologies	Required	1	Years
Experience developing ETL and ELT pipelines	Required	1	Years
Experience with Spark, GraphDB, Azure Databricks	Required	1	Years
Expertise in Data Partitioning	Required	1	Years
Experience with Data conflation	Required	3	Years
Experience developing Python Scripts	Required	3	Years
Experience training LLMs with structured and unstructured data sets	Required	2	Years
Experience with GIS spatial data	Required	3	Years

Job Tags

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