Okay, I've searched for Senior Data Engineer roles specializing in AI platforms in Inver Grove Heights, MN, requiring 5+ years of experience, proficient in Python and Terraform, and full-time positions. I have found 27 suitable openings for you.

Sure. Here's the analysis:

Job Analysis:

This Senior Data Engineer - AI Platforms role is fundamentally about bridging the gap between AI model deployment and robust, scalable cloud infrastructure within a complex agricultural client environment. The incumbent is expected to architect, operate, and optimize advanced AI platforms such as Dataiku, AWS AI/ML services, and OpenAI APIs. This means more than just technical maintenance; the engineer must ensure secure governance around sensitive model APIs and data, provide seamless scalability, and maintain uptime and performance. The role’s emphasis on infrastructure automation (Terraform, CloudFormation), container orchestration (Kubernetes/EKS), and observability tools suggests a high expectation for hands-on ownership of the platform's lifecycle—from deployment through monitoring and incident response. Success here means enabling AI-driven business outcomes reliably and securely while managing costs and ensuring compliance, especially in a regulated agricultural context. Collaboration across teams—data science, architecture, DevOps, and security—is core, underscoring that the role is as much about communication and strategic alignment as it is about technical execution.

Company Analysis:

Genesis10 operates as a respected, award-winning staffing and talent solutions firm with a broad footprint across industries, including Fortune 100 clients. As a staffing partner rather than the end client, Genesis10 plays a pivotal role in connecting skilled professionals with organizations that demand technical excellence. The company culture, inferred from its accolades related to work-life balance, career growth, diversity, and leadership, appears supportive and candidate-centric—prioritizing long-term career development and respectful candidate relationships. For the Senior Data Engineer role, this means joining through a recruiting partner that values your professional trajectory and offers opportunities for exposure to highly reputable clients and cutting-edge AI workloads. While the company fills various roles via contract and permanent models, a hybrid engagement reflects a balance of in-person collaboration and remote flexibility. Strategically, this role is likely a growth-oriented and specialized hire aimed at advancing the AI platform maturity at the client site, making it a critical linchpin who supports innovation and operational stability within a cutting-edge, cloud-native AI ecosystem.

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

• Behavioral: Tell me about a time when you had to troubleshoot and resolve a complex issue with AI platform performance or uptime. How did you approach it?
• Behavioral: Describe a situation where you collaborated across different teams (e.g., Data Science and DevOps) to deliver an AI or data engineering solution. What challenges did you face and how did you overcome them?
• Behavioral: Can you share an experience where you had to enforce security or compliance protocols in managing cloud infrastructure or AI APIs? How did you balance operational efficiency with governance?
• Behavioral: Talk about an instance when you automated infrastructure deployment. What tools did you use, and what impact did your automation have on the team or project?
• Technical/Role-Specific: How would you set up and manage secure access and governance for large language model API keys in an enterprise environment?
• Technical/Role-Specific: Walk me through your process for designing and deploying a scalable AI platform using AWS services such as Bedrock, Textract, and Comprehend.
• Technical/Role-Specific: What are your strategies for monitoring and optimizing costs (TCO) in cloud-hosted AI platforms? Can you provide an example?
• Technical/Role-Specific: Explain your experience with Kubernetes (specifically Amazon EKS) for deploying containerized AI workloads. How do you ensure high availability and observability?
• Situational: Imagine the AI platform experiences a sudden spike in API usage that risks exceeding rate limits and impacting service availability. How would you respond?
• Situational: You discover discrepancies in compliance audit logs related to AI platform usage. What steps would you take to investigate and mitigate risks?
• Situational: A new AI service is released that could enhance your current platform significantly. How would you evaluate and integrate this emerging technology while ensuring operational stability?
• Company Fit/Motivation: Why are you interested in working on AI platform engineering for an agricultural client, and how do you see your skills aligning with this sector's unique challenges?
• Company Fit/Motivation: How do you align with Genesis10’s emphasis on career growth and work-life balance? What environment helps you do your best work?
• Company Fit/Motivation: What attracts you to a contract-to-hire role at Genesis10 versus a direct hire or permanent position elsewhere?
• Questions for Interviewer: How does the client’s AI platform team currently measure success and platform maturity? What are the top priorities for this role in the next 6 months?
• Questions for Interviewer: Can you describe how collaboration typically happens between the AI platform engineering team and other stakeholders like Data Science, DevOps, or Security at the client site?
• Questions for Interviewer: What professional development or career growth opportunities does Genesis10 provide to consultants in specialized technical roles like this?