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Title: Data Engineer

Location: Richmond, VA

Hybrid:  2 days/week at the office. 

Duration: 9 months

Interview: Webcam and In-Person

Job Description :

Agentic Data Engineer to design, develop, and deploy data pipelines that leverage agentic AI that solve real-world problems.
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 processes to support agentic systems, ensure data quality and facilitate interaction between agents and data.

Responsibilities: 

• Guiding and mentoring AI engineers, helping them develop their skills and knowledge in the field.
• Leading and managing AI projects, ensuring they stay on track, meet deadlines, and the findings are actionable and relevant.
• Contributing to the creation and implementation of AI strategies that align with the organization’s goals and objectives.
• Designing and developing data pipelines for agentic systems, developing Robust data flows to handle complex interactions between AI agents and Data sources.
• Ability to use advanced mathematical modeling, statistical analysis, and optimization techniques to gather and analyze data, identifying problems and developing solutions to improve efficiency in prompts.
• Ability to train and fine tune large language models and Design and build the data architecture, including databases, data warehouses, and 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

 
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
• Strong leadership, excellent problem-solving and communication skills
• Proven experience in leading projects and teams, including the mentorship of AI engineers
• The ability to engage in critical evaluation of information, hypothesis testing, and scenario analysis.
• Flexibility in learning and adopting new technologies, methodologies, and tools to stay at the forefront of AI trends.
• 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.