Staff Product Manager

Who we are:

Founded in 2013, Ignition is the leading revenue and billing automation platform for firms and agencies to transform their sales, billing and payment processes.

Ignition 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, Ignition customers have managed relationships with over 2.4 million clients and earned $13b in revenue via the platform. Ignition's global workforce spans Australia, Canada, New Zealand, the Philippines, US and the UK.

Company Values:

We are better everyday

We work without ego

We are smarter together

We hero our customer

Where and how we work:

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.

About the Role

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: choosing the right problems and knowing whether what shipped actually worked (and what to do about it).

We're hiring a Staff Product Manager against that bar. You'll start on Payments , the ledger, the rails, the money movement, and the experience that decides whether a service business gets paid on time. It's our revenue core and the most consequential surface we have. We're not requiring you to arrive with payments expertise; we're requiring you to be the kind of builder who gets deep in a hard domain fast, and we'll expect you to be dangerous in it within a quarter.

You'll operate as the product manager and peer builder for the area: 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 engineering team and designer as one pod.

Why This Role Matters

We're raising what a product manager is accountable for. AI didn't change the job; it removed the middle of it — the spec-writing and coordination that used to camouflage weak judgment. What's left is choosing the right bets and making them land.

This seat sits on the surface where that matters most to the business. Payments is Ignition's revenue core: how well it works determines whether a firm gets paid on time, which is the promise the whole product makes. We're hiring the judgment first and backing you to learn the domain because judgment is the part we can't teach on the job.

What your day to day will look like:

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 a product area end to end – Starting with Payments: rails and payment methods, the ledger and settlement layer, payouts and reconciliation, fraud and risk controls, reporting, and the compliance surface underneath it — plus the provider relationships (Stripe today) it runs on. You own reliability and trust as much as features.

Get deep in the domain, fast – Payments is technical, regulated, and unforgiving. Your first job is to earn the judgment the domain requires — from the designer and engineers who hold it, from customers, and from the data — rather than routing every hard call to someone else.

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. The bar isn't perfect first-call accuracy; it's calibration that visibly improves.

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 work and where the friction actually sits. Partner with Key Account Managers to get the right calls booked; when that isn't moving, go direct.

Move a business outcome, not a feature list – For this area, that's payment volume, adoption, and utilisation across the base. Use quantitative and qualitative signal to find what blocks activation, deepen usage, and grow volume. 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. Learn where the blast radius sits: what can ship behind a flag to ten customers tomorrow, and what needs the slower, careful path.

Use AI to compress every step you can – Drafting artifacts, exploring data, prototyping flows, synthesising research, getting up to speed on an unfamiliar domain. 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 Ops so the product is well-adopted, well-supported, and well-understood.

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.

What you need to succeed:

7+ years of product management experience , including ownership of a complex, high-consequence system where correctness mattered and failure was expensive — financial, transactional, infrastructure, marketplace, healthcare, logistics, or similar. The domain is open; the depth is not.

A track record of getting deep in an unfamiliar domain fast – tell us about a time you were the least knowledgeable person in the room and were leading it within a quarter and what you did specifically.

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 clea