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Fieldguide is automating and streamlining assurance and audit work for cybersecurity, privacy, and financial audit practitioners. As an Audit Methodology Engineer, you will bridge audit methodology and Fieldguide's AI-powered platform, ensuring it delivers accurate, contextual, and explainable guidance that auditors can trust and that meets audit standards.
You will operationalize methodology documentation within the platform, working at the intersection of audit standards, professional judgment, and AI. Your responsibilities include:
Methodology Management: Define the structure and logic of Fieldguide's out-of-the-box methodology content. Design how audit standards (US GAAS, PCAOB, etc.) translate into methodology content and audit procedures. Structure guidance from relevant frameworks into usable, well-organized content. Identify key industry procedures, testing approaches, and practice guidance. Manage the ingestion and review process for methodology content and engagement templates. Incorporate auditor feedback from real-world usage.
AI Collaboration: Partner with AI architects and engineers to translate professional standards and practitioner judgment into prompts, workflows, and guardrails for methodology and testing agents. Work with product teams to turn audit standards into functional specifications and user workflows.
Implementation & Maintenance: Support financial audit implementation teams with bespoke methodology builds, customization, and annual updates. Ensure methodologies are implemented with appropriate quality control rigor, including version control and documentation. Monitor regulatory and industry developments. Maintain and evolve the audit knowledge base as standards change.
You must have a CPA and 5+ years of public accounting experience with strong expertise in AICPA auditing standards (GAAS), PCAOB, and audit methodology. Experience with audit technology, automation, AI-enabled tools, audit methodologies, templates, or workpapers is required. Working knowledge of quality control/quality management standards (SQMS 1, PCAOB QC standards) as they relate to methodology development is essential. You should be able to translate professional standards into structured workflows and logic, think analytically, and work cross-functionally with product and engineering teams. Interest in the intersection of audit, data, and AI is important.
Nice-to-have qualifications include experience in audit methodology or national office roles, expertise in international auditing standards, and exposure to LLMs, prompt design, or AI-assisted workflows.
