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AI Audit Trail Developer

Liam Singh

Full-time · Job · New_York

About the role

When an AI system makes a decision that affects someone's insurance premium, loan application, or medical treatment, regulators want to know exactly how that decision was made. Not approximately. Exactly. Our audit trail system captures every input, model version, feature value, and decision pathway — creating an immutable record that satisfies regulatory auditors years after the decision was made. You'll build the audit infrastructure: capturing model inputs and outputs with zero performance overhead, storing decision records in tamper-evident logs, building the query interface that auditors use to reconstruct any past decision, and designing retention policies that balance storage costs with regulatory requirements. Audit trails for AI are fundamentally different from traditional application logging. The 'decision' isn't a single function call — it's a pipeline of feature computations, model inferences, and post-processing rules. Capturing all of it without slowing down the production system requires careful engineering of asynchronous capture, efficient serialization, and intelligent compression.

Responsibilities

  • Build zero-overhead model decision capture for production AI systems
  • Design tamper-evident audit log storage with regulatory-grade integrity
  • Create query interfaces for auditors to reconstruct past AI decisions
  • Implement retention policies balancing storage costs with compliance requirements
  • Ensure audit trail completeness across multi-step decision pipelines

Requirements

  • 5+ years in systems engineering with compliance or audit experience
  • Strong Python and FastAPI skills for high-throughput capture systems
  • Kubernetes and Docker expertise for distributed logging infrastructure
  • Understanding of regulatory audit requirements for AI decision systems
  • Experience with tamper-evident storage and data integrity verification

Benefits

  • Fully remote — US East Coast hours
  • Senior compensation with equity
  • $2,500 learning budget
  • Building trust infrastructure for regulated AI

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Categories

Automation & AI Workflows MLOps & AI Infrastructure

Skills

python sql docker kubernetes aws

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

Automation & AI Workflows MLOps & AI Infrastructure

Skills

python sql docker kubernetes aws fastapi

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