Technical practice
Suggested practice: How would you architect an agentic AI platform for developer tooling?
What to coverThe role covers agent orchestration, an SDK, sandboxed runtimes, and LLM gateway infrastructure. Explain the boundaries between these components, how they interact, and where you would enforce security and maintainability.
Suggested practice: When should agent orchestration be deterministic rather than LLM-driven?
What to coverThe posting specifically mentions systems that combine both approaches. Discuss where predictable control flow matters, where LLM decisions add value, and how you would handle failures or unexpected agent behavior.
Suggested practice: How would you design safe execution for an agent that uses development tools?
What to coverSandboxing, access control, tool integration, and safe agent execution are stated concerns. Describe permission boundaries and how you would limit and inspect actions without making the tools unusable.
Suggested practice: How would you manage context for an agent working across software-development tasks?
What to coverThe posting names context engineering and context-management systems. Explain how you would select and update relevant context, manage its limits, and evaluate whether it helps the agent complete a task accurately.
Suggested practice: What responsibilities belong in an LLM gateway?
What to coverLLM gateway infrastructure is a named platform capability. As a design suggestion, discuss centralized access controls, observability, and model integration, including what should remain the responsibility of applications using the gateway.
Suggested practice: How would you design a Python SDK that other engineering teams can adopt?
What to coverThe role requires Python expertise and involves building an SDK and internal developer tooling. Discuss API clarity, extensibility, testing, and how you would learn whether the SDK works well for its users.
Suggested practice: How would you decide whether to integrate an external agent framework or build a capability internally?
What to coverThe posting calls for framework evaluation and build-versus-buy judgment. Compare security, extensibility, developer experience, maintainability, and the cost of integrating a framework into an enterprise platform.
Suggested practice: How would you evaluate and troubleshoot agent behavior in production?
What to coverThe posting seeks evaluation, observability, or quality-assurance experience, including measuring, tracing, and improving behavior. Explain what evidence you would collect, how you would investigate a failure, and how findings would inform a change.
Suggested practice: Where could AI agents fit into existing software-development workflows?
What to coverThe team supports how MathWorks plans, builds, delivers, and monitors software; CI/CD, code review, and testing infrastructure are also named. Choose a workflow and explain a bounded use case, its safeguards, and how you would assess whether it improves the workflow.
Behavioural practice
Suggested practice: Tell me about a time you turned an ambiguous technical problem into an actionable plan.
What to coverScoping cross-cutting, ambiguous work is a stated responsibility. Use a real situation, explain how you clarified constraints and divided the work, and describe the result.
Suggested practice: Tell me about a time you helped an engineer improve a design or code change.
What to coverThe role includes mentoring through code review and design collaboration. Describe the situation, the feedback or collaboration you provided, and the resulting change without overstating your individual contribution.
Suggested practice: Tell me about a time stakeholder input changed a technical roadmap or automation priority.
What to coverThe posting calls for understanding development workflows and identifying high-leverage automation opportunities. Explain whom you consulted, how you weighed the input, what you did, and what resulted.
Suggested practice: Tell me about a time you drove adoption of a technical practice across teams.
What to coverThe role involves setting patterns for AI-agent use and influencing engineering practices beyond one team. Give a real example of the situation, your approach to alignment and communication, and the outcome.
Suggested practice: Tell me about a time you explained a difficult architecture trade-off to different audiences.
What to coverThe posting emphasizes consequential technical decisions and communication with engineering and non-engineering audiences. Describe the decision, how you adapted your explanation, the actions others took, and the result.