Technical practice
Designing Scalable Agentic Architectures
What to coverExplain how you would design a production-ready AI agent system using LangGraph. Focus on state management, error handling, and ensuring the architecture remains scalable as the number of agents and complexity of workflows increase.
LLM Integration and Optimization
What to coverDiscuss your experience integrating LLMs into enterprise applications. Address how you handle model selection, prompt engineering, and the trade-offs between latency, cost, and accuracy in a high-stakes banking environment.
Agentic Orchestration with LangGraph
What to coverDescribe a scenario where you used LangGraph to manage complex, multi-step agentic workflows. Explain how you define state transitions and handle cycles or human-in-the-loop requirements within the graph structure.
Deployment and Monitoring in Kubernetes
What to coverDetail your approach to deploying AI services using Docker and Kubernetes. Specifically, explain how you incorporate monitoring tools like Arize or Dynatrace to track model performance, drift, and system health in production.
Technical Formalization of Business Requirements
What to coverProvide an example of how you translate ambiguous business requirements into a structured technical design. Suggestion: Focus on your process for defining scope, identifying necessary AI capabilities, and creating a roadmap for implementation.
Utilizing Google AI SDK
What to coverExplain how you leverage the Google AI SDK to interact with LLMs. Discuss how you manage API interactions, rate limiting, and security considerations when building applications that interface with sensitive banking data.
Implementing Speech-to-Text (STT) in AI Pipelines
What to coverDescribe how you integrate STT services into agentic workflows. Discuss the challenges of real-time processing and how you ensure high accuracy and low latency in a production environment.
Framework Evolution and Feedback Loops
What to coverAs an engineer contributing to an internal framework, how do you gather and prioritize feedback from project teams? Explain how you balance the need for new features with the requirement to maintain platform stability and standards.
Behavioural practice
Evangelizing New Technology to Stakeholders
What to coverDescribe a time you had to convince non-technical stakeholders to adopt a new framework or technology. How did you communicate the value proposition and address their concerns regarding risk and implementation effort?
Collaborating in a Multi-Disciplinary Environment
What to coverGive an example of working with diverse teams (e.g., business analysts, security, infrastructure) to deliver an AI project. How did you ensure alignment and resolve conflicting priorities?
Navigating Ambiguity and Uncharted Territory
What to coverTell me about a time you were tasked with solving a problem where no clear precedent existed. How did you approach the research, experimentation, and final solution design?
Empathy in Technical Guidance
What to coverDescribe a situation where you had to provide technical guidance to a team struggling with a new technology. How did you tailor your approach to help them succeed while maintaining project standards?