Okay, I've searched for AI & Machine Learning Engineer Manager roles in Tampa, FL within the consulting industry, full-time positions requiring 6-10 years of experience, with Python skills and experience in deploying ML workflows on cloud platforms. I have found several positions for you to review.

Sure. Here's the analysis:

Job Analysis:

This AI & Machine Learning Engineer - Manager role at EY focuses on leading technical teams to design, develop, and deploy advanced AI/ML solutions that solve complex, often unprecedented, business problems for a diverse client base. The core purpose is to bridge cutting-edge AI technology with practical, scalable outcomes that add tangible value to clients across industries, requiring deep technical expertise as well as strong client-facing skills. The role demands hands-on proficiency with Python, generative AI frameworks, ML libraries, DevOps and MLOps practices, and cloud platforms, reflecting EY’s emphasis on implementing robust, production-grade models rather than purely experimental work. Managing teams and collaborating across interdisciplinary groups highlights the importance of leadership and communication in a consulting context where client priorities and technical feasibility often require balancing. The candidate will face challenges such as rapidly evolving AI capabilities, ambiguity in client needs, and integrating AI solutions into existing enterprise systems. Success here involves consistent delivery of innovative, reliable solutions that are well-aligned with evolving client strategies and regulations, combined with fostering team growth and knowledge sharing. The role also expects agility, continuous learning, and ethical integrity, ensuring technical excellence translates into trusted, impactful advisory services.

Company Analysis:

EY is a leading global professional services firm operating in assurance, consulting, tax, strategy, and transactions, with a strong commitment to building a better working world through technology and trust. Positioned as a trusted advisor leveraging advanced AI and data insights, EY drives transformation initiatives for large, complex, and often regulated clients worldwide. This means that the AI & Machine Learning Engineer - Manager operates within a culture that values integrity, innovation, inclusivity, and agility. EY’s hybrid, team-led, leader-enabled environment demands adaptability and strong interpersonal skills to collaborate across diverse teams and geographies. The firm’s broad industry reach and global footprint offer strategic career growth opportunities but also require individuals who can navigate ambiguity and diverse stakeholder expectations. For this role, the company’s focus on ethical standards and continuous learning suggests a workplace that values not only technical excellence but also responsible AI deployment and personal development. Overall, this is a strategic hire aimed at scaling EY’s AI capabilities to meet evolving client demands and competitive market pressures, making it essential for the candidate to align with EY’s mission and be ready to contribute substantially to its innovation-led consulting practice.

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

• Behavioral: Tell me about a time when you had to manage a technical team through the development and deployment of a complex AI/ML project. How did you ensure quality and timely delivery?
• Behavioral: Describe an experience where you faced a challenging problem due to ambiguous client requirements. How did you clarify needs and drive the project forward?
• Behavioral: How have you fostered knowledge sharing and collaboration in a diverse technical team? What strategies worked best?
• Behavioral: Can you share an instance where you identified an ethical concern in an AI project and how you addressed it?
• Technical: How would you architect an end-to-end machine learning workflow on a cloud platform to ensure scalability, reliability, and maintainability?
• Technical: Explain your experience with generative AI models and frameworks such as OpenAI’s family or Langchain. How have you applied these in real-world solutions?
• Technical: Describe your approach to integrating CI/CD, MLOps practices, and DevOps tools like Git and Azure DevOps into AI model development and deployment.
• Technical: How do you evaluate and improve the performance of ML models, particularly when dealing with multi-source and large-scale data?
• Situational: Imagine a client requests a rapid AI solution with minimal data availability and high uncertainty. How would you approach the project to deliver value responsibly?
• Situational: If multiple internal stakeholders have conflicting priorities regarding a machine learning project’s functionality and timelines, how would you manage and align expectations?
• Situational: You discover a critical flaw in a deployed AI model that could affect client decisions. What immediate actions would you take, and how would you communicate with the client?
• Company Fit: Why does EY’s mission to build a better working world resonate with you, particularly through AI and advanced technology?
• Company Fit: How do you see your growth mindset and agile approach enabling you to succeed within EY’s consulting culture?
• Company Fit: What interests you most about working at EY as opposed to other consulting or technology firms?
• Candidate Questions: Can you describe the typical composition and working style of the AI and Data teams at EY? How does this role interact with other service lines?
• Candidate Questions: What key challenges or opportunities do you foresee for this role in the next 12 months given EY’s strategic priorities in AI?
• Candidate Questions: How does EY support continuous learning and career development specifically for technology leaders in AI and machine learning?