Overview
On Site
$$80/hr on C2C or $70/hr on W2
Accepts corp to corp applications
Contract - W2
Contract - 5 month(s)
Skills
Python
Data Architecture
Git
Azure Data Lake
ETL development
Azure Databricks
Azure Blob Storage
cloud computing
GIS spatial data
Data conflation
Data Partitioning
GraphDB
Spark
Vector Databases
Large Language Models (LLMs)
Azure Machine Learning
Azure AI Search
ELT Pipelines
AI Integration
Human-in-the-Loop Systems
Agentic systems
Azure OpenAI
Embedding models
Big data frameworks
Job Details
Job Title: Agentic Engineer
Location: Richmond, VA (Onsite Quarterly)
Interview: In-person/Webcam
Job Description:
- Design and develop data pipelines for agentic systems; develop robust data flows to handle complex interactions between AI agents and data sources.
- Train and fine-tune large language models (LLMs).
- Design and build data architecture, including databases 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 for high performance.
- Conduct statistical analysis to identify trends and patterns and create data formats from multiple sources.
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Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
| Skill | Required /Desired | Amount | of Experience |
|---|---|---|---|
| Understanding the Big data technologies | Required | 5 | Years |
| Experience developing ETL and ELT pipelines | Required | 5 | Years |
| Experience with Spark, GraphDB, Azure Databricks | Required | 5 | Years |
| Experience training LLMs with structured and unstructured data sets | Required | 4 | Years |
| Experience in Data Partitioning and Data conflation | Required | 3 | Years |
| Experience with GIS spatial data | Required | 3 | Years |
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