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AI Audit Trail Completeness Validator

Noah Kovacs

Full-time · Job · New_York

About the role

An AI system that cannot explain its decisions is not explainable — it is just undocumented. Explainability in production means capturing not just the model's output but the full decision trail: what data was used, which model version made the decision, what confidence threshold was applied, and whether any human review occurred. When that audit trail is incomplete, regulatory inquiries become expensive and product liability is unclear. We build the explainability infrastructure for enterprise AI systems, and audit trail completeness is a core product feature. Your job is to build the validation layer: the ML models and rule-based checks that analyze audit logs to detect gaps, inconsistencies, and compliance violations before auditors do. The validation system needs to work across diverse AI systems with different decision schemas, handling everything from credit decisions with regulatory audit requirements to HR screening systems with emerging legal obligations.

Responsibilities

  • Build audit trail completeness validation models for enterprise AI decision systems
  • Develop rule-based and ML-based gap detection for decision audit logs
  • Design completeness schemas for different AI use case regulatory contexts
  • Create dashboards showing audit trail coverage and compliance risk status
  • Implement automated alerting when audit gaps reach regulatory risk thresholds
  • Collaborate with legal and compliance teams on jurisdiction-specific requirements

Requirements

  • 3+ years in data engineering or ML engineering with compliance or audit domain experience
  • Strong SQL and Python skills for log analysis and pipeline work
  • Experience with data quality validation or completeness checking systems
  • Understanding of AI governance or regulatory compliance frameworks
  • Ability to work with legal stakeholders on technical compliance requirements

Benefits

  • Fully remote
  • Health and dental
  • 20 days PTO
  • $2,500 learning budget
  • Equity participation

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Categories

AI Product & Strategy Automation & AI Workflows

Skills

python sql pandas fastapi docker

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Job Type

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Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

AI Product & Strategy Automation & AI Workflows

Skills

python sql pandas fastapi docker statistics

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