Understand the business. Rethink the work. Make AI deliver.

Brisbane, Australia | Hybrid / embedded | Full time

Reports to: CTO / CEO

About Valont

Valont is an AI-native business services platform for small and medium businesses. We combine real-time business intelligence, AI-driven advisory, deep integrations and AI-delivered workflows to help owners understand their business and deliver the work, not just analyse it.

Part of Wattlestone, a Brisbane-based private investment firm, we acquire high-quality service firms, integrate them onto our proprietary AI platform and redesign how their services are delivered.

We are not building software that sits beside a service business. We are rebuilding the service business itself.

Why this role exists

AI transformation takes more than technology. It requires understanding how a business really works, seeing what could change and bringing people with you.

That happens inside the business, not in a strategy presentation.

You will work with the businesses we acquire and Valont's internal teams to understand their workflows and judgement, then turn that knowledge into practical AI-delivered services. You will connect the people doing the work with our technical team, staying accountable through testing, rollout and adoption.

This is a hands-on role at the intersection of business, AI and delivery

If you bring consulting or operational transformation experience, commercial judgement and practical AI skills, and want to own implementation rather than just make recommendations, this role is built for you.

What you’ll actually do

- Get inside the business. Work with owners, advisors and operational teams through real inboxes, documents, spreadsheets, systems and exceptions,



not just documented processes. Help move teams to shared systems while preserving business knowledge and customer history.
- Redesign from first principles. Start with customer outcomes and genuine constraints. Question why each step exists, remove unnecessary tasks and handoffs, and simplify what remains before automating.
- Turn opportunities into a practical plan. Quantify value across capacity, cost, service quality and growth. Agree priorities with operational and technical leaders, balancing impact, effort, risk and dependencies. Define future workflows, necessary human judgement and a phased plan that evolves with AI capabilities.
- Build and prove what you can. Use AI tools, configurable agents and automation to build proofs of concept and practical improvements. Test ideas yourself rather than sending every request to engineering.
- Translate between the business and technology. Give engineers clear requirements, real examples, exceptions and acceptance criteria. Explain technical choices and constraints in plain English.
- Be the first quality filter. Test real operating scenarios before rollout. Spot when something works technically but is confusing, incomplete or unsuitable for its users.
- Own implementation and change. Coordinate onboarding,



training and rollout with operational leaders and domain experts. Surface changes to responsibilities and capacity early, address concerns and stay close until new ways of working are embedded.
- Close the loop and help shape the Valont way. Track adoption, service quality and realised benefits. Resolve issues and turn successful approaches into repeatable service models and implementation playbooks, improving them with each acquisition.

The mindset that matters

- We're building an autopilot, not a copilot. But putting an agent on every step of an outdated process is not transformation either.
- Start with the outcome, not the workflow you inherited. What does the customer need? How would we deliver it reliably if we designed the service today, with AI available from the start?
- Existing processes are evidence, not a blueprint. Some steps protect quality or manage risk; others compensate for disconnected systems, late information or old workarounds. Your job is to tell the difference.
- If a team asks for a faster reporting spreadsheet, understand the decision it supports. Surfacing an exception and triggering the right action might remove the spreadsheet and the weekly reporting task entirely.
- Remove what is unnecessary. Simplify what remains. Then automate where it adds value.
- Preserve the purpose of necessary controls, professional oversight and human approvals. Validate new approaches and handle sensitive business data responsibly.
- Success is not the number of agents deployed. It is delivering a better outcome with less work required in the first place.

The level of technical ability we’re looking for

Strong, hands-on AI skills are esse

📌 AI Transformation Lead (Brisbane)
🏢 Valont
📍 Brisbane