Technical practice
Designing for Multi-Agent Orchestration
What to coverExplain your approach to designing multi-agent systems where different agents handle distinct tasks like trading, support, or compliance. Discuss how you manage inter-agent communication, task delegation, and conflict resolution to ensure a cohesive user experience.
Implementing RAG for Financial Accuracy
What to coverDescribe how you would architect a Retrieval-Augmented Generation (RAG) pipeline to ensure high accuracy for crypto-specific queries. Focus on how you handle data freshness, source verification, and minimizing hallucinations in a high-stakes financial environment.
AI Evaluation Frameworks
What to coverWhat metrics and evaluation frameworks do you prioritize for conversational AI in a regulated industry? Address how you balance automated testing with human-in-the-loop evaluation to ensure product quality and safety.
Ensuring Auditability in Agentic Systems
What to coverIn the context of internal operations like risk and fraud, how do you design agentic systems to be fully traceable and regulatorily defensible? Discuss the logging, explainability, and governance layers required for audit compliance.
Safety Architecture and Governance
What to coverHow do you design a safety architecture that prevents unauthorized actions or data leakage in an AI-driven platform? Suggest how you would implement guardrails that are configurable across different global markets.
Tool Use and API Integration
What to coverDiscuss the challenges of enabling LLMs to interact with external tools and APIs for trading or account management. How do you ensure secure, reliable tool execution while maintaining a seamless conversational flow?
Scaling AI Infrastructure
What to coverAs a Director, how do you approach building shared AI infrastructure that supports both user-facing assistants and internal operational agents? Focus on the trade-offs between centralized platform services and domain-specific customization.
Managing LLM Latency and Performance
What to coverWhat strategies do you employ to manage the latency and performance trade-offs inherent in complex agentic workflows? Address how you optimize for real-time user interactions without compromising the depth of the AI's reasoning.
Behavioural practice
Leading AI Strategy in Regulated Markets
What to coverDescribe a situation where you had to balance aggressive AI product innovation with strict regulatory requirements. How did you align stakeholders and ensure the product remained compliant while still delivering value?
Managing Complex Product Roadmaps
What to coverProvide an example of how you have managed a product roadmap that spanned multiple, highly technical AI initiatives simultaneously. How did you prioritize resources and communicate progress to executive leadership?
Building Trust in AI Products
What to coverTell us about a time you had to earn user or institutional trust for a new AI-driven feature. What specific actions did you take to demonstrate reliability, transparency, and safety?
Cross-Functional Collaboration
What to coverDescribe a time you led a cross-functional team to transform an inefficient manual process into an automated, agent-driven system. How did you handle resistance to change and ensure the final output met operational standards?
Navigating Technical Ambiguity
What to coverShare an example of a time you had to make a high-stakes product decision based on emerging or ambiguous AI technology. How did you validate your hypothesis and mitigate risks before full-scale implementation?