VDOT - Agentic Data Engineer
Apply NowCompany: Aloden, Inc.
Location: Richmond, VA 23223
Description:
Title/Role: VDOT - Agentic Data Engineer
Location: 1401 E Broad St. Richmond, VA 23219
Work Arrangement: Hybrid
Job Description:
Agentic Data Engineer to design, develop, and deploy data pipelines that leverage agentic AI that solve
real-world problems
The Virginia Department of Transportation'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.
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.
Must Have Skills:
Location: 1401 E Broad St. Richmond, VA 23219
Work Arrangement: Hybrid
Job Description:
Agentic Data Engineer to design, develop, and deploy data pipelines that leverage agentic AI that solve
real-world problems
The Virginia Department of Transportation'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.
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.
Must Have Skills:
- Understanding the Big data Technologies, Required: 1 y
- Experience developing ETL and ELT pipelines, Required 1Y
- Experience with Spark, GraphDB, Azure Databricks, Required 1Y
- Expertise in Data Partitioning, Required: 1Y
- Experience with Data conflation, Required: 3Y
- Experience developing Python Scripts, Required: 3Y
- Experience training LLMs with structured and unstructured data sets, Required: 2Y
- Experience with GIS spatial data, Required: 3Y