Senior Product Manager, Agent Builder
Confirmed on the employer's own hiring board on Nov 10, 2026. First seen by Alion on Nov 6, 2026.
We are looking for a skilled and passionate Senior Product Manager to join our Agent Builder team in our NYC office. Working in a high-growth scale-up, you’ll have the unique opportunity to drive innovation at scale while contributing to a company transforming the world of audit and finance.
About the role:
Agent Builder is where firms turn their own methodology and knowledge into AI agents, and manage those agents for their whole life, from definition to retirement. A generic agent knows nothing about how a firm works. Its methodology, guidance, templates and past work are what make an agent behave like one of the firm's own people, and that knowledge and context layer is what sets our agents apart.
You'll own the Agent Builder product in Alwin, our agentic platform for audit and finance. That means the definition model behind an agent, how firms test and publish agents they can trust, and how those agents are versioned, governed and retired at scale. There's no playbook for letting professionals build, run and govern production agents in a regulated domain. You'll help write it.
This is a product role with a strong technical bent, and we welcome candidates from product or technical PM backgrounds. You'll work closely with a new engineering team in New York, with our Agent Runtime, Evals and Document Intelligence teams in Amsterdam, and with the customers and domain experts who define what a good agent looks like.
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.
What you'll own
Knowledge and context: how a firm's methodology, guidance, templates and prior work are captured, kept current, permissioned and served to agents at the moment they need them
Definition: the authoring experience and the definition model that turn a procedure into a multi-step agent: steps, tools, knowledge sources, thresholds and human-in-the-loop gates
Test and publish: how builders evaluate an agent against real cases before it ships, and the review and approval it passes before it reaches the Agent Library
Run and observe: tracing what an agent did on a live engagement, which knowledge it used and why
Govern, version and retire: permissions, change history, approvals, rolling out new versions without breaking work in progress, and retiring agents and outdated knowledge cleanly
What You Will Do:
Set the product direction and roadmap for Agent Builder, and make the trade-offs explicit
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
Define how we prove an agent works, with evals on real cases and results reported with a stated method, not a headline accuracy number
Treat lifecycle as product: versioning, approvals, rollout and retirement designed in from day one
Keep confidentiality central: what an agent learns from one customer's work must never reach another
Prototype flows yourself before writing specs, then write short specs and decision memos engineers can build from
Work with forward-deployed engineers, solutions architects and go-to-market teams, and turn what they learn on enterprise rollouts into platform capabilities rather than one-offs
Run discovery with the people who govern agents at customer firms, and change the plan when the evidence says so
What You Bring:
Experience as a PM on platform or developer-facing products that other people build on, from a product or a technical PM background
Experience shipping LLM or agent features in production. You understand context and retrieval, tool calling, evals, human review in the loop and non-determinism, and why "it worked in the demo" isn't evidence
Comfort with data models and system design: definition schemas, versions, immutable records, permissions, and how objects relate to each other
Experience with products that have a lifecycle customers depend on: versioning, permissions, release and deprecation
Enough technical depth to make architecture trade-offs with engineering leads and challenge designs credibly
Discovery discipline: you separate what customers said from what you hoped they said
Hands-on use of AI tools in your own work, including prototyping
Clear, concise writing
What sets you apart
Knowledge of audit or accounting, from practice or from building products for auditors, finance teams or other expert users in regulated fields
Familiarity with how firms validate and govern tools before relying on them, and with quality management standards such as ISQM 1
Experience with knowledge management or enterprise search: ingestion, retrieval, document-level permissions, keeping content fresh
Experience with low-code or configuration products, workflow designers, rule engines or DSLs
Agent evaluation in practice: datasets, offline and online experiments, failure classification, measuring the effect of context on quality
Running design-partner programmes with large enterprise customers
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)
Panel Presentation (60 minutes, online)
Leadership interview (30 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.