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Jobs(31,365)/AI Engineer Role(760)/fieldguide (31) - SOX AI Specialist (Contractor)
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fieldguide

fieldguide - SOX AI Specialist (Contractor)

Remote - USA$125k - $166k+ Equity4d ago
RemoteNAAI EngineerCoachingCPA

Requirements

• At least four years of hands-on control testing experience in SOX compliance, internal audit, or internal controls, with direct responsibility for control design and testing. • Broad experience across a range of control types, industries, and firms, with clear expertise in business process control testing. • The ability to consistently explain why a test step, exception, or conclusion passes or fails and to turn that reasoning into clear evaluation criteria. • Strong written reasoning: you can explain workflows and decisions step by step and turn professional judgment into clear rules, edge cases, and review criteria. • A high degree of comfort and hands-on experience using AI tools, writing prompts, and working with agentic harnesses. • Comfort operating in ambiguity, testing ideas quickly, and changing your approach when the evidence does not support it. • Availability for the expected time commitment during the initial engagement. • WHAT WE’D LOVE TO SEE • Experience at the senior or manager level reviewing SOX workpapers or coaching testers. • A CPA, CIA, or similar relevant credential. • Experience across multiple companies, clients, industries, or control environments. • Familiarity with both business process controls and ITGCs. • Demonstrated interest or experience in creating AI workflows or tools of any kind.

Responsibilities

• Partner closely with engineering, product, and design teams to translate real-world SOX testing processes into scalable product capabilities. • Co-develop AI agents with AI engineers to execute detailed SOX testing by translating SOX testing methodology into specific guidance, decision rules, and examples. • Work hands-on with AI agents: write and refine prompts, run controls and evidence through testing workflows, evaluate outputs, and document failure modes. • Analyze risk and control matrices and test plans to identify opportunities for improved agentic testing. • Develop stress-test scenarios, review and assess AI agent performance, and create detailed error analyses and evaluation criteria.

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