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Datasnipper
Datasnipper

Engineering Manager (Excel Agents)

Job summary
Permanent contract
Netherlands
Occasional remote
Salary: Not specified
Experience: > 5 years
Skills & expertise
Observation skills
Technical aptitude
Coaching and mentoring
Azure
Excel
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Datasnipper
Datasnipper

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Questions and answers about the job

The position

Job description

  • We are looking for a skilled and passionate Engineering Manager to join our Excel Agents Team in the Amsterdam office
  • Working in a bootstrapped and profitable scaleup, you’ll have the unique opportunity to lead a team building the intelligence layer that automates the assurance lifecycle and brings AI directly into the workflows of auditors worldwide
  • Lead an engineering team through outcomes, not tasks; set clear goals with the team and trust them to figure out how
  • Make the team measurably better; raise the engineering bar, grow engineers into bigger problems, and address performance issues directly when they arise
  • Drive a step change in what the team can do with AI; not just shipping faster, but tackling harder problems, raising quality, and expanding what the team can credibly own
  • Lead the team responsible for building AI-powered agents that automate assurance workflows, from risk assessment and evidence gathering to control testing and documentation generation
  • Own the technical direction and architecture of the Excel Agent platform, ensuring agents are reliable, observable, secure, and effective in real customer workflows
  • Guide the team in designing and scaling agentic systems that combine LLMs, document intelligence, business workflows, and human oversight
  • Partner closely with Product, Design, and other Engineering teams to shape the roadmap and translate customer needs into impactful AI experiences
  • Make the architectural and technical calls that shape the team’s systems, and stay close enough to the code to do so credibly
  • Lead the adoption of AI-assisted engineering practices and contribute to how DataSnipper leverages AI across the broader engineering organization
  • Help shape the team’s scope as it evolves, including expanding ownership areas and standing up new teams when needed
  • Foster a culture of experimentation, learning, documentation, and operational excellence

Preferred experience

  • Minimum 5 years as a software engineer with a passion for building scalable, reliable, and high-quality software systems
  • Experience operating systems in production with a focus on reliability, observability, and maintainability
  • Track record of leading engineering teams that build with AI day to day, and making those teams measurably more effective as a result
  • Strong product aptitude; can challenge product framing, translate customer needs into technical solutions, and make effective roadmap tradeoffs
  • An empowerment style of management; you lead through outcomes and trust, not by assigning tasks
  • Strong understanding of software architecture, distributed systems, APIs, and cloud native development
  • Experience building AI-powered products or platforms, ideally involving LLMs, agentic workflows, document processing, or automation systems
  • A track record of growing engineers and creating high-performing teams
  • At least 3 years of leading and managing engineering teams, driving performance, growth, and professional development through hands-on mentorship, feedback, and goal setting
  • Strategic thinker; able to shape product direction, technical direction, and team scope, not just execute on what’s handed down
  • Entrepreneurial mindset with the ability to thrive in a fast-moving scale-up environment
  • Experience building and deploying GenAI applications in production
  • Experience with agentic systems, orchestration frameworks, or AI-powered workflow automation
  • Experience with Python and modern backend development practices
  • Familiarity with Azure AI services, document intelligence, and cloud infrastructure
  • Experience working in startups or scaleups
  • Experience in fintech, audit technology, or document-intensive workflows
  • Experience with observability and monitoring tools
  • Strong understanding of testing strategies and engineering quality practices

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