Agentic Data Engineer

Govserviceshub; Richmond (VA); On-site; USD 90,000 - 120,000; Full time

Job summary

The Virginia Department of Transportation is seeking an Agentic Data Engineer to design and deploy data pipelines leveraging agentic AI. This role involves architecting complex data flows and managing AI data operations on cloud platforms. Candidates should have experience in big data technologies, Python scripting, and GIS data analysis. A Bachelor's or Master's in a relevant field is required.

Qualifications

• Minimum 1 year experience with Spark/Databricks and data architecture on Azure.
• At least 3 years of Python scripting and spatial data experience.

Responsibilities

• Design and manage robust ELT pipelines and data architectures.
• Train and fine-tune large language models (LLMs).
• Collaborate with AI engineers and data scientists.

Skills

Python Scripting

Big Data Technologies

GIS and Spatial Data Analysis

Data Partitioning Strategies

AI Agent Frameworks

Education

Bachelor’s or Master’s in Computer Science

Bachelor’s or Master’s in Data Science

Bachelor’s or Master’s in AI

Tools

Spark

Databricks

GraphDB

Azure Services

Job description

Richmond, United States | Posted on 05/09/2025

Note: Candidates with Department of Transportation or state agency experience are strongly preferred.

• Each candidate must submit a government-issued ID (Driver’s License or Passport) and provide three professional references (names, official emails, and phone numbers).

Job Description:

The Virginia Department of Transportation (VDOT) is seeking an Agentic Data Engineer to design, develop, and deploy data pipelines that leverage agentic AI to solve real-world transportation data problems. The role involves architecting complex data flows, training large language models, integrating human-in-the-loop feedback systems, and managing AI data operations on cloud-based platforms.

Specialty Areas:

• Agentic AI Integration – Designing pipelines that enable dynamic interactions between AI agents and diverse data systems.

• LLM Training & Optimization – Preprocessing structured/unstructured data, training LLMs, and enhancing performance with feedback loops.

• GIS and Spatial Data Processing – Working with road topology, geo-location data, and spatial correlation using lat/long datasets.

• Big Data & Cloud Engineering – Leveraging Spark, GraphDB, Databricks, and Azure services for high-volume data processing.

• AI + Transportation Domain Expertise – Applying agentic solutions for what-if analysis, forecasting, correlation modeling, and decision recommendations.

Responsibilities:

• Design and manage robust ELT pipelines and data architectures (lakes, databases).

• Implement vector databases and embedding models for retrieval-based AI.

• Build feedback loops for human-in-the-loop learning in AI systems.

• Train and fine-tune large language models (LLMs).

• Ensure efficient data storage/retrieval through partitioning and performance optimization.

• Collaborate with AI engineers and data scientists on preprocessing, modeling, and deployment.

• Work with GIS spatial data for route correlation and road network analysis.

• Apply machine learning and statistical techniques to analyze and format multi-source data.

Skill Matrix:

Skill

Experience (Years)

Big Data Technologies (Spark, Databricks, GraphDB)
1+

ELT / ETL pipeline development
1+

Data Partitioning Strategies
1+

Python Scripting
3+

Data Conflation
3+

Training LLMs with structured/unstructured data
2+

GIS and Spatial Data Analysis
3+

Azure Services (AI, OpenAI, ML, Blob, Data Lakes)
1+

AI Agent Frameworks & Vector Databases
1+

Cloud & Machine Learning Fundamentals
1+

Mandatory Requirements:

• Strong understanding of data engineering and agentic AI concepts.

• Minimum 1 year experience with Spark/Databricks and data architecture on Azure.

• At least 3 years of Python scripting and spatial data experience.

• Proven ability to build pipelines integrating AI agents with large datasets.

• Experience with LLM training and vector databases.

Qualifications:

• Bachelor’s or Master’s in Computer Science, Data Science, or AI.

• Prior experience with Department of Transportation data and systems.

• Familiarity with embedding models, Graph DBs, and cloud AI services.

• Strong communication, problem-solving, and collaborative skills.

Submission Requirements:

• Three professional references (Names, official emails, phone numbers)