Product Manager

About Big Time

Big Time is a PSA platform built for professional services firms. Our customers use Big Time to scope and sell work, staff it, track time and expense, bill their clients, and see where their margin actually comes from. Thousands of consulting, IT, engineering, and accounting firms run their business on the platform.

The Financial Core pod owns the accounting engine underneath the platform: the project accounting subledger, the cost model, revenue recognition, WIP and unbilled balances, period close, and the integrations that tie all of it back to a firm's general ledger.

This is the surface a controller reconciles against and an auditor has to accept. When it is right, a firm can confidently run its finances with us. When it is wrong, finance stays in spreadsheets and deals stall in evaluation. The pod carries real demand from day one, and the person leading it will be making calls that shape the platform for years.

You will own the roadmap, the specification quality, and the outcome for that surface, working alongside an engineering lead, a designer, and a team of engineers who sit with you.

This is also an underlying foundational layer for our next generation, AI-native platform. You will have the opportunity to build something brand new, while leveraging the expertise, data, customer knowledge and codebase from our existing platform.

• The project accounting subledger. Trial balance, subledger detail, aging, GL reconciliation, and the controls around period open, soft close, and hard close.

• Revenue recognition. ASC 606 support covering performance obligations, transaction price allocation, and recognition by method, including percent complete on cost, hours, or progress, along with milestone, ratable, and on-invoice.

• The cost model. Employee cost, contractor cost, vendor and pass-through spend, and the margin visibility that sits on top of all of it.

• WIP, unbilled, and deferred balances treated as reportable, reconcilable objects rather than numbers derived at report time.

• GL and ERP integrations. Starting with Quick Books and extending to the major mid-market and enterprise accounting systems, with bidirectional reconciliation and error handling a finance team can trust.

• AI-native finance workflows. Agents that run the recognition cycle, drive the close checklist, reconcile subledger to GL, and explain every exception in language an accountant accepts.

• Write specifications precise enough that an engineer can build from them and a controller would recognize them as correct. Your written work is the artifact the pod aligns on.

• Spend real time with controllers, CFOs, revenue accountants, and accounting managers at services firms, then turn what you hear into requirements with defensible priority.

• Track regulatory and accounting-standard changes on an ongoing basis, and represent their downstream compliance impact in roadmap decisions.

• Make the prioritization calls for your surface and defend them with evidence rather than volume.

• Partner daily with engineering and design inside and across pods. Trade-offs get settled in the room, not through an approval chain.

• Define acceptance criteria, including for agent behavior, and hold the quality line before anything ships to a customer close cycle.

• Work closely with Sales, Customer Experience, and Finance so the roadmap reflects what wins deals and what keeps customers.

• Own the financial contract other pods build against, and review any feature across the platform that creates or changes financial data.

• 6+ years of product management for the PM level, or 4+ years for the Senior PM level, on a B2B SaaS product with genuine domain depth.

• A track record of shipping complex, backend-heavy capability that customers adopted, not just features that launched.

• Strong written communication. You can hold a position in a document and change your mind in public when the evidence moves.

• Comfort operating with ambiguity and a bias toward getting to a decision quickly.

• Experience working directly with engineering on data models and system design, and enough technical…