Agentic Engineer

Agentic Engineer

USC/GC Holder

Duration of contract - 6-12+ months

Hybrid role in Richmond, VA.

Resumes must be 4 pages or less than 5 pages, or they won't be considered.

‼Also, I want to stress that only local candidates will be considered. If possible,
send proof of residence with your resume
- driver's license, state-issued , or copy of rental agreement/deed are strongly preferred (one page); no utility bills will be accepted.

Our client is seeking a highly skilled Agentic Engineer to design, develop 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
-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.

Qualifications

-Strong data engineering fundamentals.

- Experience with big data frameworks such as Apache Spark and Azure Databricks.
-Ability to train LLMs using structured and unstructured datasets.
-Understanding of graph databases.

- Experience with Azure services including Blob Storage, Data Lakes, Databricks, Azure Machine Learning, Azure Computer Vision, Azure Video Indexer, Azure OpenAI, Azure Media Services, and Azure AI Search.
-Proficient in determining effective data partitioning criteria and implementing partition schemas using Spark.
-Understanding of core machine learning concepts and algorithms.
-Familiarity with cloud computing concepts and practices.
-Strong programming skills in Python and experience with AI/ML frameworks.
-Proficiency in working with vector databases and embedding models for retrieval tasks.
-Expertise in integrating with AI agent frameworks.

- Experience with cloud-based AI services, especially Azure AI.
-Proficient with version control systems such as Git.
-Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.