Okay, I've searched for Engineer II positions specializing in Generative AI in Richmond, VA, requiring a Bachelor's degree in Computer Science, 2+ years of experience with Python and large language models, with full-time hybrid work arrangements. I have found 73 available roles matching your criteria.

Sure. Here's the analysis:

Job Analysis:

The Engineer II - Generative AI role at CarMax is designed for a technologist who combines solid software engineering capabilities with domain expertise in cutting-edge AI, specifically generative AI and large language models (LLMs). The core purpose of this position is to design, develop, evaluate, and deploy AI-driven solutions that enhance CarMax’s omni-channel customer experience. This involves not only building systems that generate content but also implementing robust pipelines for testing, performance monitoring, and continuous improvement. The responsibilities suggest that the successful candidate must be both technically autonomous and collaborative, translating complex business requirements into scalable AI solutions that handle unstructured data effectively. The inclusion of prompt engineering, cloud services like Azure OpenAI, and evaluation frameworks underlines a need for a dynamic learner comfortable with iterative experimentation. Soft skills such as communication and influencing team culture are equally vital, indicating this role transcends technical execution to shape team norms and technical direction. The challenges inherent in this job revolve around navigating the rapidly evolving AI landscape, ensuring model reliability, and integrating AI responsibly within large-scale consumer-facing systems. Success in this role will be measured by the quality, accuracy, and reliability of generative AI applications deployed, the ability to innovate in model tuning and evaluation, and the achievement of clear improvements in customer engagement facilitated by AI capabilities within the first year.

Company Analysis:

CarMax operates as a pioneering leader in the used car retail industry, distinguished by its innovation-driven approach focused on honesty, transparency, and customer-centric experiences. As the nation’s largest used car retailer, CarMax combines scale with a commitment to technological innovation, as exemplified by the opening of technology hubs and investment in AI-driven solutions. The company culture appears to emphasize inclusion, continuous learning, and collaboration across functions, fitting for a hybrid work environment that fosters innovation while maintaining strong community values. The role’s placement within a growing technology innovation center suggests an environment that balances stability with forward-looking disruption, supporting engineers who bring new digital experiences into a traditional sector. Candidates joining here are expected to thrive in a setting where technical excellence intersects with business impact, working cross-functionally to solve complex problems at scale. Strategically, this role aligns with CarMax’s broader ambition to maintain market leadership by enhancing digital customer interactions with AI, thus serving as a growth-oriented hire pivotal to the ongoing transformation of retail experiences fueled by intelligence and automation.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you used generative AI or large language models to solve a complex problem. What approach did you take, and what was the outcome?
• Behavioral: Describe an instance where you had to influence a team’s technical direction or culture. How did you approach this, and what impact did it have?
• Behavioral: Can you share a situation where you had to work independently on a technical project with minimal oversight? How did you ensure success?
• Behavioral: Explain how you managed conflicting priorities or requirements across stakeholders when developing an AI-driven solution.
• Technical: How would you approach designing and evaluating a generative AI pipeline to ensure content accuracy and system reliability for a customer-facing application?
• Technical: What techniques do you use for prompt engineering to improve large language model responses? Can you give an example?
• Technical: Describe your experience with deploying AI applications in cloud environments, particularly using Azure OpenAI and Azure AI Search. What challenges did you face?
• Technical: How do you implement testing and CI/CD practices to maintain the quality of AI software solutions in production?
• Situational: Imagine you detect a significant drop in the performance of a generative AI model after deployment. How would you investigate and address this issue?
• Situational: If you were assigned to optimize an existing chatbot that uses LLMs to improve both response relevance and speed, what steps would you take?
• Situational: Suppose a key stakeholder requests a feature that conflicts with best practices in AI ethics or reliability. How would you handle the conversation and decision?
• Company Fit: Why are you interested in working at CarMax, particularly within its AI engineering team?
• Company Fit: How do you see your skills and experiences aligning with CarMax’s mission of delivering honest and transparent customer experiences through technology?
• Company Fit: How do you prioritize inclusion and collaboration when working in a hybrid, innovation-focused environment?
• Questions for Interviewer: Can you describe how the GenAI team integrates with other departments at CarMax to influence product development?
• Questions for Interviewer: What are the biggest technical challenges CarMax faces in scaling AI solutions across its customer experience platforms?
• Questions for Interviewer: How does CarMax support continuous learning and career growth for engineers working in emerging AI technologies?