Staff Product Manager, Payment

1 нед. назад

AustraliaWorldwideLeadHybrid

ai tooling

Lead evolution of payments product focusing on money movement and customer experience.

О компании

Founded in 2013, is the leading revenue and billing automation platform for firms and agencies to transform their sales, billing and payment processes. automates proposals, engagement letters, invoicing, payments and workflows in a single AI-powered platform, empowering 8,500+ businesses to sell, bill and get paid for their services with ease. To date, customers have managed relationships with over 2.4 million clients and earned $13b in revenue via the platform. 's global workforce spans Australia, Canada, New Zealand, the Philippines, US and the UK.

Обязанности

We're seeking a Staff Product Manager to own the evolution of 's Payments product, the ledger, the rails, the money movement, and the customer experience that decide whether a service business gets paid on time and knows where the money is.
This is not a roadmap stewardship job. The pace of building software has changed: a product manager working inside a tight pod with engineers and a designer, all using modern AI tooling, now moves from problem to shipped product in days or weeks rather than quarters. We've rebuilt R&D around that pace, which means engineering capacity is no longer the constraint, product judgment is. Your job is to make sure that speed lands on the right problems, in a domain where a mistake moves real money.
You'll operate as the product manager and peer builder for Payments: identifying impactful opportunities, framing the problem, sizing the bet, building alongside the team if necessary, validating and shipping to real customers early, and staying on the work after launch until the business numbers move. You'll report to the SVP, Product, and work day to day with the payments engineering team and designer as one pod.
Own both ends of the product arc – We think of the PM job as two bookends. The front bookend : finding and assessing the opportunities that matter, then shipping to learn — getting a real thing in front of real customers fast enough to find out whether you were right. The back bookend : driving adoption and utilisation after launch, or diagnosing why it isn't landing and pushing the fix, enhancing it, changing it, or being the human forcing function across GTM, Support, and Customer Success until it lands. Most of the middle, spec ceremony, ticket grooming, coordination overhead, is gone.
Own the Payments platform end to end - Payment rails (ACH, PAD, card, and what comes next), the ledger and settlement layer, payouts and reconciliation, payment methods and tokenisation, fraud and risk controls, reporting, and the compliance surface (KYC/AML, PCI, tax) underneath it all.
Set the appetite and cut scope to it - Before a cycle starts, size the bet: the expected impact of the problem and a time budget proportional to it, with the reasoning posted in the open. Fixed time, variable scope. You make the must-have vs. nice-to-have calls inside that budget and own them when trade-offs surface mid-build. In payments the impact math is often directly computable, which makes this the team where calibration is most testable and most expected to improve.
Build inside the pod as a peer, not above it - You work alongside engineers and a designer with direct decision-making authority. When the pod needs a call, you make it. When the pod is ready to ship, you ship.
Ship to real customers early and let them change your mind – Get the working build in front of firms as soon as it's usable and own the feedback loop directly. Iteration speed is the edge; defending the original plan is not.
Develop and hold deep customer understanding yourself – Talk to firms directly about how they invoice, chase, reconcile, and get paid, and where the friction and distrust actually sit. Partner with Key Account Managers to get the right calls booked; when that isn't moving, go direct.
Drive payment volume, adoption, and utilisation – Use quantitative and qualitative signal to find what blocks activation, deepen usage, and grow volume across the base and adapt what you're building when the numbers say to.
Be fast where it's safe and careful where it isn't – Payments carries risk other surfaces don't; a ledger error is not a bug you roll back quietly. Know precisely where the blast radius sits: what can ship behind a flag to ten customers tomorrow and what needs the slower, careful path to launch.
Use AI to compress every step you can – Drafting artifacts, exploring data, prototyping flows, synthesising research, reconciling messy operational detail. Artifacts still matter for alignment and shared understanding, but the one that used to take two days should now take an hour.
Partner cross-functionally – Work with Product Marketing, Sales, Customer Success, Support, and Risk so the product is well-adopted, well-supported, and well-understood.
Optimise systems and scale – Continuously improve the reliability, compliance, and performance of global payments infrastructure in partnership with external providers (Stripe today and potentially others as we grow).
Define and own how your success is measured – State the hypothesis before the build and capture the learning after it. We measure the speed and quality of the learning loop — cycle time from problem to customer, iteration on what you learn, appetite calibration, and the business outcomes that follow, not features shipped, documents produced, or meetings attended.

Будет плюсом

multi-currency, multi-entity, or cross-border payments experience; regulated-market exposure (AUSTRAC, KYC/AML programs, PCI scope reduction); accounting or practice-management domain knowledge (QBO, Xero); and a willingness to ship a PR when it helps — a flag, a small blocking bug, a working prototype. Welcome, not expected; there's no merged-PR quota in this role.
We may use AI enabled tools to support parts of our recruitment process, such as improving efficiency in scheduling and note taking. These tools are used responsibly and never replace human decision-making, all hiring decisions are made by our people.
We aim to keep the process transparent, respectful of your time, and as smooth as possible.
We encourage you to apply even if you don’t meet every requirement, experience comes in many forms, and diverse perspectives make our teams stronger.
is an equal opportunity employer. If you require accommodations during the recruitment process or need materials in an alternative format, please contact careers@.

Другое

We are better everyday
We work without ego
We are smarter together
We hero our customer
We are open to candidates based in Sydney with full Australian work rights. We operate in a hybrid model, giving you flexibility to work from home, from a shared workspace, or a mix of both.
7+ years of product management experience, with 3+ years in payments or fintech – payment rails, authorisation and settlement flows, ledger design, or transaction infrastructure. You've owned a money-movement surface, not just a feature adjacent to one.
Real technical fluency in payments infrastructure – rails (ACH, PAD, card, local schemes), providers (Stripe, Adyen, Plaid or similar), and the failure modes: reconciliation drift, settlement timing, chargebacks, retries, idempotency, partial failure.
Proven ability to deliver high-availability financial systems that hold compliance, risk, and a genuinely good user experience at the same time.
Technical depth – you can read code, reason about systems, and engage engineers as a peer. A formal engineering background isn't required; engineering being a black box to you is disqualifying.
AI already in your daily workflow – Claude, Cursor, or comparable tools aren't something you're asking permission to use, and you have opinions about which to reach for, when.
Comfort defining quality for AI-assisted features – you can say what "good" means for output that isn't deterministic, design a test set that proves it, and validate against real customer use.
Demonstrated use of data and experimentation to generate insight, prioritise effectively, and measure impact — as a habit, not a phase.
Strong customer empathy and a track record of translating qualitative and quantitative signal into clear product decisions.
Adept at structuring ambiguous problems , making trade-offs, and aligning people around what matters most.
Clear, concise communication that creates clarity and accountability across technical and non-technical audiences.