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DataSnipper

Excel-based AI-driven audit automation platform

Engineering Manager - Agent Builder

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 of experience 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 context engineering and retrieval; understanding of control loops, tool calling, grounding, and evaluation sufficient to challenge team designs.
  • Experience building platform products with a lifecycle, including versioning, permissions, release, and deprecation for customer-built products.
  • Strong fundamentals in software architecture, distributed systems, application programming interfaces, and cloud-native development.
  • Strong product aptitude, including challenging framing, making roadmap trade-offs, and focusing on customer success.
  • Hands-on fluency with artificial intelligence coding tools and agentic harnesses, and experience improving a team's effectiveness through their use.
  • Ability to lead across time zones and offices and communicate clearly in writing.

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 measurably each quarter.
  • Own the technical direction of Agent Builder end-to-end while remaining close enough to the code to make informed technical decisions.
  • Build the context layer that grounds agents in a firm's methodology, including how knowledge is captured, maintained, permissioned, and retrieved, and how its impact is demonstrated.
  • Determine the appropriate level of flexibility and guardrails for agent builders.
  • Design versioning, approvals, rollout, and sunsetting into the product lifecycle.
  • Make evaluation, observability, and auditability integral to the product.
  • Partner with Agent Runtime, Evals, Document Intelligence, Product, Design, and audit methodology experts to deliver a coherent platform.
  • Shape how the engineering organization uses artificial intelligence to take on harder problems and improve its work.
  • Work with Forward Deployed Engineers, Solution Architects, and go-to-market teams to turn enterprise rollout learnings into platform capabilities.

Desired Qualifications

  • Knowledge management or enterprise search experience, including ingestion, chunking, embeddings, hybrid retrieval, document-level permissions, and keeping content current.
  • Experience with knowledge graphs or structured representations of policies, procedures, and rules.
  • Experience building low-code or configuration products, workflow designers, rule engines, or domain-specific languages.
  • Practical agent evaluation experience, including datasets, offline and online experiments, failure classification, and measuring how context affects quality.
  • Experience in regulated domains such as audit, financial services, or healthcare, where traceability, approvals, and access control are requirements.
  • Experience operating governance at scale, including permissions, approvals, and change control across enterprise customers, teams, and thousands of users.
  • Python, Azure, and observability tooling.
  • Domain experience in audit methodology, accounting, or financial technology.

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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