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Point72 Asset Management·AI Engineer·Online Assessment (OA)·Intermediate

Intermediate
Apr 2026

Summary

Took an online assessment for an AI Engineer role at Point72 and one of the questions was a multi-part prompt engineering scenario. Time management was a real issue and the later sub-questions were pretty rough.

Questions Asked (1)

Q1

Design a prompt to filter news for an Olympic champion athlete, given a specific coaching scenario. The question had five sub-parts.

Product Sense & IdeationTechnical Trade-offsAdaptability & Ambiguity
Author's notes

Made the mistake of typing everything manually instead of using AI to generate and paste, which the platform actually encouraged.

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AI HintsAI Generated

Suggested Approach

Clarify the coaching scenario and the athlete's information needs, then design a prompt that filters news for relevance, reliability, and timeliness. Structure your answer around the five sub-parts, explicitly addressing product sense, technical trade-offs, and adaptability to ambiguity.

Pro tip: Anchor your design in the athlete's decision-making context—what actions will they take based on the news? This shows product sense and ensures the filter is purpose-driven, not just technically sound.

1. Clarify the Scenario and Requirements

Ask questions to understand the athlete's sport, the coaching context, and what decisions the news will inform. Define success criteria for the filter, such as precision, recall, and latency.

2. Define Filtering Criteria and Data Sources

Specify relevance dimensions (e.g., sport, event, athlete name, coaching relevance) and select credible news sources. Consider paywalls, language, and regional coverage.

3. Design the Prompt Structure

Craft a prompt that instructs the model to extract and filter news based on the criteria, including output format (e.g., JSON with title, source, relevance score, summary).

4. Address Technical Trade-offs

Discuss trade-offs between precision and recall, real-time vs. batch processing, and cost vs. accuracy. Propose metrics to evaluate the filter's performance.

5. Plan for Adaptability and Ambiguity

Outline how the prompt can be adapted to different sports, athletes, or changing news landscapes. Include fallback strategies for ambiguous or low-confidence cases.

Key Points to Mention

  • Relevance filtering based on athlete's sport, upcoming competitions, and coaching goals
  • Source credibility and bias detection to avoid misinformation
  • Timeliness and real-time updates for time-sensitive decisions
  • Handling ambiguity: ambiguous athlete names, multiple sports, or evolving news stories
  • Evaluation metrics: precision, recall, F1, and user feedback loops
  • Scalability and cost considerations for processing large news volumes

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.