Technical practice
How would you design an AI agent to automate part of early-stage power-project due diligence?
What to coverSuggested preparation: Describe how you would define the human task, identify required inputs, and decide which steps can be automated versus reviewed by an expert. Discuss how you would make the agent’s outputs traceable and handle missing or conflicting information.
How would you choose between Agent SDK, Messages API, and LangGraph for an agent workflow?
What to coverThe posting asks for familiarity with all three, but does not specify how Paces uses them. Suggested preparation: Explain the capabilities you would compare, such as workflow control, integrations, observability, and operational complexity, rather than assuming a particular stack.
How would you evaluate and troubleshoot an AI agent deployed in production?
What to coverSuggested preparation: Discuss testing against representative tasks, monitoring failures and output quality, and tracing a bad result through inputs and agent steps. Explain when you would revise the workflow, add a safeguard, or route a case to human review.
How would you build an ETL pipeline for data-intensive project-development software?
What to coverSuggested preparation: Cover validation, changing source data, repeatable processing, and how downstream features would know which data they used. Explain trade-offs between processing speed, data quality, and maintainability without assuming a particular data source.
How would you use Python and SQL to diagnose a slow data-backed feature?
What to coverSuggested preparation: Explain how you would locate the bottleneck across application code, queries, and database access before changing anything. Discuss query plans, data volume, and the trade-off between a targeted fix and a broader redesign.
How would you scale an end-to-end feature as platform traffic grows?
What to coverThe role explicitly includes backend, database, infrastructure, and scaling work. Suggested preparation: Describe how you would measure the constraint, protect reliability during a rollout, and choose improvements based on observed load rather than assuming a specific architecture.
How would you validate automation intended to enable a new modeling capability?
What to coverSuggested preparation: Define the model’s intended decision or output with domain experts, then compare automated results with appropriate reference cases. Discuss how you would expose uncertainty and decide when the capability is ready for use.
How would you translate siting, interconnection, or permitting expertise into software requirements?
What to coverPaces says engineers work closely with power and permitting experts on features for these workflows. Suggested preparation: Explain how you would map a current decision process, clarify exceptions, and confirm that the resulting feature preserves important expert judgment.
If a feature used geospatial data, what data-quality and engineering issues would you examine?
What to coverGeospatial experience is a bonus, not a stated requirement. Suggested preparation: Discuss location accuracy, coordinate-system consistency, data freshness, and how errors could affect a siting-related result.
If automation touched energy-grid modeling, how would you establish its boundaries?
What to coverEnergy-grid modeling or utility experience is listed as a bonus; the posting does not define a specific model. Suggested preparation: Explain how you would agree on inputs, assumptions, validation cases, and points requiring expert review before relying on an automated result.
Behavioural practice
Tell me about a time you made progress without complete specifications.
What to coverSuggested preparation: Use a real situation, the questions you resolved or assumptions you made, and the actions you took to unblock the work. State the result, including anything you had to revise when more information became available.
Tell me about a time you iterated on a feature with a domain expert.
What to coverSuggested preparation: Describe the situation, how you elicited the expert’s reasoning, and what you changed after feedback. Give the result without claiming expertise or outcomes you cannot substantiate.
Tell me about a time you helped a product team make a roadmap trade-off.
What to coverSuggested preparation: Set out the competing needs, your technical input, and how the decision was made. Explain the result and what you learned about balancing delivery with longer-term work.
Tell me about a time you took ownership of an end-to-end feature.
What to coverSuggested preparation: Identify the situation, your responsibilities across implementation and release, and how you coordinated with others. Describe the result and how you addressed any issue discovered after delivery.
Tell me about a time you responded to a production reliability problem with a team.
What to coverSuggested preparation: Describe the impact, your specific diagnostic and coordination actions, and the observed result. Include a follow-up change or lesson if there was one, without presenting a hypothetical incident as personal experience.