Role description
DataSnipperWe are hiring an Engineering Manager in our New York office to lead the Agent Builder team behind Alwin, our Agentic Automation Platform for audit and finance.
About the role:
Agent Builder is where firms turn their methodology and knowledge into agents, and manage those agents for their whole life: from definition to retirement. A generic agent knows nothing about how a firm audits. The firm's methodology, guidance, templates and past work are what make an Alwin agent behave like one of their own people, and that knowledge and context layer is our key differentiator. There is no playbook for letting auditors build, run and govern production agents in a regulated domain. You and your team will write it..
Why DataSnipper?
The hardest AI problems aren't about getting an answer fast. They're about getting one people can trust.
We believe trust is essential to how society works. Every day, we rely on information that's been independently verified, from financial statements to the products we buy, to the sustainability claims companies make. Behind that trust are audit and finance professionals who examine evidence, verify information and hold organizations accountable.
At DataSnipper, we build AI solutions that empower those professionals. By making evidence easier to trace and verify, we help them focus on the judgment and expertise that make their work so important.
For our product and engineering team, this is where things get exciting. In audit, a plausible answer isn't good enough. Every output has to be explainable and traceable back to its source. We've just launched a brand new agentic platform, Alwin by DataSnipper. AI agents running in the cloud across hundreds of documents at once, reasoning across PDF, Word and Excel, with a full audit trail behind every step. There are lots of greenfield problems ahead, and real room to shape what we build and how we build it.
And we build at scale. More than 600,000 professionals across 3,000+ organizations in 175 countries rely on DataSnipper, including Fortune 500 companies, government agencies and all Big Four audit firms. In 2025 alone, the DataSnipper platform delivered more than $1.4 billion in productivity savings to is customers. Backed by a $100 million Series B led by Index Ventures, at a $1 billion valuation, and as proud members of 1% for the Planet, we care about how we grow, not just how fast.
If you want to build AI that professionals trust with work that really matters, this is your chance to help shape the future of audit and finance and do the best work of your career along the way.
The Scope
Your team owns the full agent lifecycle, with knowledge at its core.
Knowledge & context: the firm's methodology, guidance, templates, prior-year workpapers and engagement context, curated, permissioned and served to agents at the moment they need it.
Define: the authoring experience and definition model that turn a procedure into a multi-step agent: steps, tools, knowledge sources, thresholds and human-in-the-loop gates.
Test & publish: evaluating an agent against real cases before it ships, with review and approval before it reaches the Agent Library.
Run & observe: launching agents on engagements, and tracing what they did, which knowledge they used and why.
Govern, version & sunset: permissions, change history and approvals; rolling out new versions without breaking in-flight work; deprecating and retiring agents and outdated knowledge cleanly.
What You Will Do
Lead through outcomes, not tasks. Set clear goals and trust the team to find the how.
Build the team. Hire, grow and retain senior engineers in New York, and make the team measurably better every quarter.
Own the technical direction of Agent Builder end-to-end, and stay close enough to the code to make the hard calls credibly.
Make knowledge the differentiator. Build the context layer that grounds agents in a firm's own methodology: how knowledge is captured, kept current, permissioned and retrieved, and how we prove it improved the result.
Get the abstraction right. Decide how much power builders get and where the guardrails sit, so agents are flexible enough to encode real methodology and consistent enough to trust.
Treat lifecycle as product. Versioning, approvals, rollout and sunsetting are what make firms trust agents at scale. Design them in from day one.
Ship agents firms can rely on. Make evaluation, observability and auditability part of the product, not an afterthought.
Work across Alwin. Partner with Agent Runtime, Evals, Document Intelligence, Product, Design and audit methodology experts, many of them in Amsterdam, to deliver one coherent platform.
Set the bar for AI-assisted engineering. Not just shipping faster, but taking on harder problems, and shaping how DataSnipper engineering uses AI.
Working closely with Forward Deployed Engineers, Solution Architects and GTM teams, turning what they learn on enterprise rollouts into platform capabilities rather than one-offs
What You Bring
3+ years leading engineering teams, on top of 5+ years as a software engineer
An empowerment style of leadership and a track record of hiring and building high-performing teams
Hands-on experience with agentic or LLM systems in production, including context engineering and retrieval: you understand control loops, tool calling, grounding and evaluation well enough to challenge your team's designs
Experience building platform products with a lifecycle: versioning, permissions, release and deprecation for things customers build on
Strong fundamentals in software architecture, distributed systems, APIs and cloud-native development
Strong product aptitude: you challenge framing, make roadmap trade-offs, and care about whether customers succeed with what you ship
Hands-on fluency with AI coding tools and agentic harnesses, and a team that is measurably better for using them
Comfortable leading across time zones and offices, with clear written communication
Nice to Have
Knowledge management or enterprise search: ingestion, chunking, embeddings, hybrid retrieval, document-level permissions, keeping content fresh
Knowledge graphs or structured representations of policies, procedures and rules
Experience building low-code / configuration products, workflow designers, rule engines or DSLs
Agent evaluation in practice: datasets, offline and online experiments, failure classification, measuring the impact of context on quality
Experience in regulated domains (audit, financial services, healthcare or similar), where traceability, approvals and access control are requirements
Governance at scale: running permissions, approvals and change control across many enterprise customers, teams and thousands of users
Python, Azure and observability tooling
Domain experience in audit methodology, accounting or fintech
What We Offer
Be part of one of the fastest-growing, profitable unicorn scale-ups with a global impact
Equity (Stock Appreciation Rights) to share the company's success and growth
Flexible paid time off
Comprehensive medical and dental coverage
401K match
Paid parental leave
Company-sponsored lunch
Hybrid mode of work (at least 3 days onsite in our New York City office)
Access to continuous learning and development initiatives to grow your skills
Engage with a vibrant international team spread across five global offices
Access to the mental health and wellness platform
Multiple social activities for team building, including company-wide events like DataSnipper GO, where global teams come together
Recruitment Process
Recruitment Screen (30 minutes, online)
Hiring Manager Interview (30 minutes, online)
System design interview (60 minutes, online)
Product Insight Discussion (60 minutes, on-site)
Final Interview (30 minutes, online)
At DataSnipper, we believe great ideas come from different perspectives, experiences, and backgrounds. We are committed to building an inclusive workplace and providing every candidate with a fair and equitable hiring experience.
Our hiring decisions are merit-based and grounded in the skills, experience, potential, and capabilities relevant to the role.
We welcome applicants regardless of age, race, ethnicity, nationality, gender, gender identity or expression, sexual orientation, religion, disability, or any other characteristic that makes you, you.
What matters to us is what you can bring to the role, the team, and DataSnipper. 🚀