monō ai | Sydney, Australia | Full-time | Client-facing, with regular in-person work at our Sydney office and customer sites

Own the deal. Get inside the business. Sell the first change that will actually hold.

monō ai is leading the Applied AI category in Australia. Our GTM team, Deployment Strategists and Forward Deployed Engineers (FDEs) are leading the next wave of AI customer transformation: getting inside how businesses operate, deploying capability into real workflows and proving measurable outcomes. We are a platform company with a distinctive blend of consultancy and skilled services. We are not just one of those things-we bring all three together to make AI work in production.

Experience with outcomes-based pricing is a real advantage: for example, connecting an Applied AI engagement to a measurable reduction in the cost of processing a mortgage loan application, rather than selling only software seats or delivery days.

The distance between an AI strategy and a changed way of working is where most enterprise value is lost. Our enterprise, multi-model AI orchestration platform and small pods of senior operators and engineers close that gap inside clients’ businesses. We build on client infrastructure, work alongside the people who run the process and prove value through production outcomes.

We are looking for a direct, quota-carrying Account Executive to create and win upper-mid-market and lower-enterprise business. You will sell the platform and the scoped work that gets it into use-but success here demands more than sales-cycle management. You must be able to diagnose an unfamiliar operation, test whether an AI deployment will improve it, assemble the coalition to act and stay close to the evidence after the contract is signed.

You own the commercial process and account; Deployment Strategists and FDEs partner with you on transformation and technical delivery.

What you will own

➔ Create and close new business. Build a targeted account plan, develop your own pipeline, engage economic buyers and run complex, multi-stakeholder deals through security, procurement, legal and signature. Set a clear commercial path for platform, deployment services and expansion; forecast honestly.

➔ Diagnose the business, not just the brief. Learn how the client creates value across revenue, cost, capacity, risk and customer experience.



Go from executive priorities into the frontline workflow: people, decisions, systems, handoffs, exceptions, incentives and controls. Separate the stated AI request from the operating constraint underneath it.

➔ Build a value case that survives scrutiny. Establish baselines and accountable owners. Distinguish cash savings from released capacity, revenue upside from aspiration and reduced risk from an unproven claim. Make assumptions, trade-offs and success measures explicit to the buyer. Where appropriate, translate that case into outcomes-based commercials with a defined metric, measurement method and agreement on what is within our control.

➔ Align the people who must make change real. Map sponsors, operational owners, technical decision-makers, risk and security approvers, users and blockers. Run working sessions that advance decisions rather than simply collect requirements. Secure the client access and commitments needed to move beyond a pilot.

➔ Shape a viable first deployment. Partner closely with Deployment Strategists and Forward Deployed Engineers to prioritise a bounded, high-value first use case, scope a credible statement of work and define the evidence for release, adoption and business impact. Speak confidently about AI behaviour and evaluation, data access, integrations, security, latency, cost and human-in-the-loop controls-while deferring detailed engineering decisions to the people responsible for the build.

➔ Turn a win into demonstrated value. Remain accountable for the executive relationship and commercial narrative while the pod owns implementation. Learn what production evidence says about usage and operating outcomes; recommend scaling, narrowing, pivoting or stopping. Expand only when delivery capacity, adoption and the economics support it.

➔ Build the 0→1 playbook. Bring field learning back to Product and Delivery, develop repeatable discovery and qualification practices, and keep opportunity plans and next steps crisp.



This is not a role with a mature territory and prewritten answers.

What you bring

➔ A record of personally originating and closing complex B2B platform or technical-solution deals with upper-mid-market or enterprise buyers. You can show how you built consensus across business, technology and risk stakeholders-not only that you made quota.

➔ Deep curiosity about how businesses actually operate, and the ability to move between an executive investment case and the details of a frontline process. You can challenge an unsupported value claim or recommend a smaller first step without losing trust.

➔ Applied-AI technical credibility: working knowledge of agents and LLMs, APIs and integration, data quality and permissions, evaluation, reliability, auditability, security, latency, cost and human control. You can explain constraints clearly and know when a specialist should take the lead.

➔ Experience or aptitude for selling software plus a defined implementation or transformation engagement, translating a business outcome into a viable commercial scope and accountable delivery path.

➔ High energy, disciplined self-sourcing and the resilience to operate in a startup building its GTM motion from 0→1. You take ownership when the deal, the deployment or the value thesis becomes difficult.

Helpful, not required: experience designing or selling outcomes-based pricing; a consulting or operating background; experience scoping and selling professional services; hands-on AI or product experience; work in regulated, security-sensitive or operationally complex sectors.

Why monō

Client data stays under client control; our platform is model-agnostic and our senior pods stay close to the outcome. Outcomes-based pricing experience will be a real benefit: imagine a mortgage broker measuring a reduction in cost per completed loan application and, where appropriate, building commercials around that verified result-not just licences or implementation effort.

Tell us about a complex deal you opened and closed, the underlying workflow problem you uncovered, and-if relevant-how you tied the commercial model to a measurable customer outcome.

If your evidence is strong but your background does not tick every preferred box, please apply. We are committed to a fair and inclusive hiring process.

📌 Senior Account Executive, Applied AI (Southern Sydney)
🏢 monō ai
📍 Southern Sydney