8116 - Midtown Office - 2220 W. Broad Street, Richmond, Virginia, 23220
CarMax, the way your career should be!

MINIMUM QUALIFICATIONS:

• Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Experience using large language models (LLMs) and prompt engineering with search retrieval frameworks for chatbot implementations
• 2+ years of experience in one or more of the following areas: software development, cloud computing, systems engineering, or machine learning/artificial intelligence
• Basic Knowledge developing and debugging in Python, and experience with scripting languages such as shell scripts
• Ability to positively influence team norms, culture, and technical vision

PREFERRED QUALIFICATIONS:

• Familiarity with fine-tuning and performance evaluation techniques for pretrained models
• Experience with Python package development
• Excellent communication skills, adapting to various audience types

SOFTWARE ENGINEERING SPECIFIC QUALIFICATIONS AND REQUIREMENTS:

• Exposure developing generative AI applications using Azure OpenAI Service
• Exposure with information retrieval services such as Azure AI Search
• Usage of development tools to design prototyping, prompt engineering, testing, and evaluation of LLM-based applications
• Experience in DevOps practices, testing frameworks, and CI/CD
• In depth knowledge developing and debugging in Python
• Experience with scripting languages such as shell scripts
  Work Location and Arrangement: T his role will be based out of the Richmond, VA Technology Innovation Center or Dallas Technology Hub in Plano, TX and have a Hybrid work arrangement.
  Work Authorization: Applicants must be currently authorized to work in the United States on a full-time basis. Sponsorship will not be considered for this specific role.

• Ability to work independently to develop, evaluate, and deploy new capabilities for our customers utilizing Generative AI models like large language models (LLMs) with scalable LLM system evaluation that measures performance and accuracy
• Comfortable with unstructured data processing to extract content for business value
• Drive learnings by experimenting with and learning AI new technologies and implementation frameworks
• Participate in requirements gathering discussions that translate into internal discussions for identifying technical implementations
• Develop and optimize pipelines, tools, and infrastructure to support and continuously improve service reliability
• Execute testing suites and report defects or performance anomalies, define severity and priority for each for resolution