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DataSnipper

Excel-based AI-driven audit automation platform

Engineering Manager - Evidence Request Management

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • At least 3 years of experience leading engineering teams, in addition to at least 5 years as a software engineer.
  • An empowerment-oriented leadership style and a track record of hiring and building high-performing teams.
  • Hands-on experience with agentic or large language model systems in production, including control loops, tool calling, human-in-the-loop processes, and evaluation.
  • Experience building workflow-heavy products with multi-step state, notifications, and permissions, ideally for users outside the customer's organization.
  • Strong fundamentals in software architecture, distributed systems, application programming interfaces, and cloud-native development.
  • Strong product aptitude, including challenging problem framing, making roadmap trade-offs, and focusing on customer success.
  • Hands-on fluency with artificial intelligence coding tools and agentic harnesses, and experience making a team measurably better through their use.
  • Comfort leading across time zones and offices, with clear written communication.

Responsibilities

  • Set clear goals and empower the team to determine how to achieve them.
  • Hire, grow, and retain senior engineers in New York, and improve the team's performance each quarter.
  • Own the technical direction of Evidence Request Management end-to-end and stay sufficiently close to the code to make technical decisions credibly.
  • Build conversational agents that represent audit firms professionally, resolve client issues in plain language, and identify questions that need an auditor.
  • Work with audit experts to encode evidence standards for each request type and measure how effectively the agent identifies problems.
  • Determine which actions agents may take autonomously, which require auditor approval, and how to make every action toward a client traceable.
  • Build resilient long-running systems, including event-driven agents and workflow state that handle partial deliveries, re-requests, deadline changes, and engagement-period rollovers.
  • Measure cycle time, follow-up volume, and first-time-right evidence, and improve the client experience as well as the firm's experience.
  • Partner with Agent Runtime, Document Intelligence, Evals, Product, Design, and audit experts to deliver a coherent platform.
  • Set standards for AI-assisted engineering and shape how DataSnipper engineering uses AI.

Desired Qualifications

  • Experience with durable workflow engines such as Temporal or long-running, event-driven production systems.
  • Experience with document processing, including optical character recognition, classification, structured extraction, and quality metrics.
  • Experience with conversational artificial intelligence for external users, including support agents or customer-facing assistants, with attention to tone, safety, and escalation.
  • Experience with case-management, ticketing, or client-portal products, and email, file-sharing, or enterprise resource planning integrations.
  • Practical experience with agent evaluation, including datasets, offline and online experiments, and failure classification.
  • Experience in regulated domains such as audit, financial services, or healthcare, where traceability, approvals, and access control are required.
  • Experience with enterprise-scale governance, including permissions, approvals, and data access across customers and their clients.
  • Experience working closely with Forward Deployed Engineers, Solution Architects, and go-to-market teams to turn enterprise rollout learnings into platform capabilities.
  • Experience with Python, Azure, and observability tooling.
  • Domain experience in audit, including prepared-by-client processes or engagement operations, accounting, or fintech.

About the Company

DataSnipper

Excel-based AI-driven audit automation platform

DataSnipper provides a subscription-based automation platform that runs inside Microsoft Excel to automate audit and finance tasks. Its Excel add-in uses AI and OCR to extract data from PDFs and documents, reconcile items, and create auditable links back to source documents; features include Table Snip, Document Matching, Financial Statement Check, and DocuMine for in-Excel document querying. DataSnipper serves large professional firms, Fortune 500s, and government agencies across 175 countries, with tiered seat-based pricing. Its goal is to cut manual data work, speed verification, and allow audit and finance professionals to focus on higher-value analysis while scaling to enterprise customers.

Company size
201-500
Company stage
Series B
Total funding
$100M
Headquarters
Amsterdam, Netherlands
Founded
2017

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