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ai prompt engineering llm data extraction fund analysis

πŸ“‹ Description

  • Ensure AI-generated fund reports meet institutional standards and catch gaps.
  • Shape product by identifying missing analysis and scoring logic issues.
  • Collaborate with engineering and AI teams to translate domain knowledge into features.
  • Audit document classification and extraction for DDQs, PPMs, and decks.
  • Improve scoring and benchmarking models; refine methodology.
  • Define what good looks like; build rubrics and reference guides.

🎯 Requirements

  • 3–6 years in institutional fund diligence (consultant, LP allocator, or fund-of-funds).
  • Deep fluency across fund documents: DDQs, PPMs, pitch decks, quarterly reports, capital call notices, side letters, K-1s.
  • Multi-strategy exposure across at least 3 of: venture, growth equity, buyout, credit, real estate, infrastructure, hedge funds, secondaries.
  • Strong analytical writing; ability to articulate fund-level insights concisely.
  • Pattern recognition for red flags; identify attribution gaps or non-standard terms.
  • Comfort with technology; articulate AI needs and work with engineers; familiarity with AI/LLM capabilities a plus.

🎁 Benefits

  • Equity upside in a company building institutional AI tooling.
  • Remote in the US; full-time role.
  • Foundational hire; build the fund intelligence quality practice.
  • Small, technical team that ships fast; no bureaucracy.
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