Technical practice
Designing Resilient FastAPI Services
What to coverExplain your approach to structuring a FastAPI application for production. Discuss how you handle dependency injection, middleware for observability, and ensuring async performance when integrating with external LLM APIs.
Architecting Multi-Agent Pipelines
What to coverDescribe how you design a multi-agent system from first principles. Address how you manage state between agents, implement tool-calling mechanisms, and ensure deterministic logic is separated from non-deterministic LLM outputs.
Handling AI System Failure Modes
What to coverHow do you implement error boundaries and retry logic in AI-driven workflows? Discuss strategies for observability in production when dealing with unpredictable LLM responses or latency in agentic chains.
Database and State Management in AI Apps
What to coverWhen building AI systems that require dynamic context discovery, how do you choose between PostgreSQL, Redis, or vector stores? Explain your rationale for data modeling to support long-term scalability.
Frontend Integration for AI Products
What to coverGiven the requirement for React and Next.js, how do you handle real-time updates or streaming responses from an AI backend? Describe your experience managing UI state when the backend is performing long-running agentic tasks.
LLMOps and Evaluation Infrastructure
What to coverWhat is your process for evaluating prompt performance and model outputs in production? Suggest how you would build a lightweight evaluation framework to track regressions as you update prompts or model versions.
Deployment and Infrastructure on GCP
What to coverDescribe your experience deploying Python services to GCP. Specifically, how do you manage CI/CD pipelines and GitOps workflows to ensure reliable deployments to Cloud Run?
Custom AI-Assisted Development Workflows
What to coverThe role emphasizes AI-assisted development. Describe a specific workflow you have customized using tools like Cursor or Claude Code to improve your coding velocity and code quality.
Behavioural practice
Navigating Ambiguity in Client Requirements
What to coverDescribe a time you were given a vague requirement by a client. How did you translate that into a concrete technical design, and what steps did you take to ensure your solution aligned with their business goals?
Managing Client Communication and Pushback
What to coverTell me about a situation where you had to push back on a client's technical request. How did you explain the trade-offs or risks, and how did you maintain a positive relationship while ensuring the system's integrity?
Self-Directed Learning in Unfamiliar Domains
What to coverGive an example of a project where you had to learn a new technology or domain quickly to solve a problem. What was your process for getting up to speed, and how did you validate your understanding?
Ownership of End-to-End Systems
What to coverProvide an example of a system you owned from architecture to production. What were the most significant technical challenges you faced, and how did your design decisions impact the system's long-term maintainability?