Technical practice
Designing a Model Gateway for Enterprise AI
What to coverExplain the architectural considerations for a Model Gateway that handles multi-model routing, load balancing, and standardized API access. Discuss how you would implement rate limiting, authentication, and cost tracking across different LLM providers while maintaining low latency.
Observability Frameworks for Generative AI
What to coverHow do you design an observability stack specifically for LLM-based applications? Focus on tracking prompt latency, token usage, hallucination rates, and drift, and explain how these metrics integrate into an enterprise operational dashboard.
Architecting AgentOps Patterns
What to coverDescribe the infrastructure requirements for supporting autonomous AI agents in production. Address challenges related to state management, tool execution environments, and the orchestration of multi-step reasoning chains.
Model Evaluation and Lifecycle Management
What to coverWhat is your approach to building a reusable evaluation framework for AI models? Discuss the trade-offs between automated benchmarks and human-in-the-loop evaluation, and how you ensure these evaluations are integrated into a CI/CD pipeline.
Scalability in Distributed AI Systems
What to coverWhen designing platforms for high-throughput inference, how do you balance model optimization techniques like quantization or pruning against the need for model accuracy? Suggest strategies for scaling these services in a cloud-native environment.
Security and Governance in AI Platforms
What to coverHow do you incorporate 'Responsible AI' and security requirements into the platform architecture? Discuss strategies for data privacy, preventing prompt injection, and ensuring compliance with enterprise governance standards during the design phase.
Build vs. Buy Decision Framework
What to coverWhen evaluating emerging AI frameworks or commercial platforms, what criteria do you use to recommend a 'build' versus 'buy' strategy? Focus on long-term maintainability, vendor lock-in, and alignment with existing enterprise architecture principles.
Architecture Governance and Review Boards
What to coverDescribe your experience preparing technical proposals for Architecture Review Boards (ARB). How do you effectively communicate complex AI platform trade-offs to non-technical stakeholders or senior management to secure approval?
Behavioural practice
Cross-Functional Collaboration
What to coverDescribe a time you had to align competing requirements from security, operations, and engineering teams for a platform project. How did you facilitate the discussion to reach a consensus that satisfied all stakeholders?
Navigating Technical Ambiguity
What to coverTell me about a situation where you had to define the architecture for a new, emerging technology area with little existing documentation. How did you validate your approach and ensure the design was scalable for the enterprise?
Influencing Technical Direction
What to coverProvide an example of when you had to convince a team or leadership to adopt a specific architectural pattern or technology. What data or evidence did you use to support your recommendation and address their concerns?
Managing Operational Excellence
What to coverDescribe a scenario where you identified a significant bottleneck or reliability issue in a platform you were responsible for. What steps did you take to diagnose the root cause and improve the system's operational resilience?