Technical practice
Designing Scalable Agentic AI Architectures
What to coverExplain how you would design a multi-agent system using Microsoft Foundry or similar frameworks. Focus on how you manage state, inter-agent communication, and scalability within a cloud-native environment.
Implementing Gen AI Ops and Monitoring
What to coverDescribe the lifecycle of a production AI application, specifically focusing on Gen AI Ops. Discuss how you would implement monitoring and security using tools like Microsoft Sentinel to ensure model performance and safety.
Cloud-Native Application Modernization
What to coverHow do you approach modernizing a legacy application to a cloud-native, event-driven architecture? Discuss the trade-offs between microservices and monoliths in the context of integrating AI capabilities.
Responsible AI in Enterprise Workflows
What to coverWhat strategies do you use to ensure Responsible AI principles are embedded into a customer's solution design? Address how you handle bias, transparency, and safety guardrails during the Proof of Concept phase.
Technical Pre-sales and Proof of Concept Strategy
What to coverWhen leading a Proof of Concept (PoC), how do you define success metrics with a customer? Explain how you balance technical feasibility with the business outcomes required to drive production deployment.
Resolving Technical Blockers in AI Deployments
What to coverDescribe a scenario where you encountered a significant technical blocker during an AI implementation. How did you diagnose the issue, collaborate with engineering teams, and communicate the resolution to the customer?
Orchestration and Semantic Kernel
What to coverExplain the role of orchestration in AI applications. Discuss how you utilize Semantic Kernel to bridge the gap between LLMs and existing enterprise data or business logic.
Containerization and Deployment Patterns
What to coverDiscuss your experience with containerization in the context of deploying AI models. How do you ensure consistent performance and security across development, staging, and production environments?
Behavioural practice
Influencing Technical Decision Makers
What to coverDescribe a time you had to influence a skeptical technical stakeholder to adopt a new architecture or AI solution. What was the situation, how did you present your technical case, and what was the outcome?
Leading Collaborative Technical Engagements
What to coverProvide an example of a hackathon or workshop you led that resulted in a tangible business outcome. Detail your role in facilitating the event and how you ensured the participants achieved their technical goals.
Managing Conflicting Technical Requirements
What to coverTell me about a time when a customer's requirements conflicted with technical best practices or security standards. How did you navigate this tension to reach a secure and scalable solution?
Continuous Learning in a Rapidly Evolving Field
What to coverThe AI landscape changes quickly. Describe a specific instance where you had to rapidly acquire and apply new knowledge to solve a customer problem. How did you validate your understanding and apply it effectively?