Why This Role Stands Out
This hybrid AI Product Manager role offers a unique opportunity to innovate within a leading hospitality technology platform, directly impacting operational efficiency and profitability for venues across Australia and New Zealand. If you thrive in a fast-paced environment, enjoy hands-on customer discovery, and are eager to shape the future of AI in the hospitality sector, this position is for you. You will have the chance to turn customer problems into shipped results in weeks, making this an exciting prospect for ambitious product leaders.
Quick Overview
Job Description
H&L is a leading hospitality technology platform serving the food & beverage and hospitality sectors across Australia and New Zealand. With more than 30 years of industry experience, H&L delivers an integrated platform spanning commerce, payments, operations, inventory, workforce management and reporting that helps hotels, pubs, restaurants, bars, clubs, cafes, liquor retailers and event venues operate efficiently and profitably.
Our platform aggregates transactions across every sale point (terminal, mobile, QR, online ordering, and increasingly voice and agentic channels), connects front of house commerce with back of house operations, advanced reporting, and integrates with more than 150 hospitality technology partners. H&L's deep sector expertise enables operators to focus on delivering exceptional guest experiences while we focus on the platform underneath that makes it possible.
The OpportunityH&L is moving its platform to the cloud and building AI into every layer of the venue: guest ordering, reservations and voice, the floor, the back of house, payments and intelligence. We work at startup pace across several products at once, and we need product people who turn a customer problem into a shipped, measured result in weeks.
The AI Product Manager works inside the product and engineering team and reports to the Head of Product Engineering & AI. You will spend real time in venues, prototype with AI tools before engineers commit, write the evals that decide when an AI feature is ready, and take each release to market with launch content you largely automate. Success is measured by venues live, adoption, and revenue from what you ship.
Key Responsibilities 1. Customer Discovery & Definition- Spend time in venues every week with operators, chefs, floor staff and head office teams to see how the work is actually done
- Turn what you learn into one page specs with the problem, a measurable outcome, and the value to the venue in dollars
- Prioritise hard with the Head of Product Engineering & AI and drop work that will not move adoption or revenue
- Prototype working solutions with AI coding and design tools (Claude Code, Cursor, Lovable or equivalents) before engineering time is committed
- Write the evals, test sets and acceptance criteria that show when an AI feature, such as voice booking, demand forecasting or anomaly detection, is ready to release
- Work with engineers in the pod through build, test and release, and own the detail: edge cases, data quality and the experience on every device
- Design for an API and MCP first platform, so partners and agents can act on H&L data and forecasts
- Own the delivery system end to end: the pod and sprint rituals, showcases, release notes, and the AI development rituals such as eval reviews and agent change logs, so the Head of Operations no longer runs them
- Configure and own Jira or the tool we choose: the hierarchy from roadmap to epics to stories, workflows, dashboards, and one roadmap that leadership and sales read as the source of truth
- Run the feedback loop every week: support tickets, pilot feedback and sales requests into the backlog, with what changed reported back to customers
- Automate the grunt work with agents: status updates, release notes, meeting summaries and backlog hygiene
- Run each launch end to end: positioning, demo, pricing page, onboarding guide and release communications, produced with AI and checked by you
- Recruit and run design partner pilots, take each one to a first paying venue, and hand Sales a repeatable pitch
- Measure adoption and revenue after launch and report them weekly with the next action
- The role does not write requirements for others to build. You build alongside engineers from prototype to release.
- The role is not desk based. Most of the insight comes from venues and customers, and you go to them.
- Junior does not mean supervised step by step. You are given a problem and the room to solve it.
- A degree in computer science, engineering or data science, or the equivalent shown in what you have built. Up to three years in product, engineering, data, consulting or a startup is preferred, and a strong graduate will be considered
- You have built and shipped something real, such as a product, a startup, an open source project or a hackathon entry, and you can show it to us
- Hospitality experience counts strongly in your favour, yet is not required
- You write code in Python or TypeScript, query data in SQL, work with APIs, and are comfortable with cloud basics on AWS or equivalent
- You can set up a delivery tool such as Jira or Linear from scratch, with the roadmap and reports a leadership team actually reads
- You use AI coding tools every day and can build a working prototype in a day
- You understand how large language models, prompts, tool use, retrieval and agents work, and how to test them with evals
- You can sit with a customer, ask the right questions and turn the answers into a decision
- You size value in dollars, make trade offs on evidence, and understand how software and payments businesses make money
- You write clearly and briefly, and your specs, demos and messages need no rework
- Your attention to detail is exceptional: numbers reconcile, edge cases are covered and releases go out clean
- You hold a strong, well argued view on where hospitality and software are heading, and you change it when the evidence changes
In your first 90 days you will have:
- Shipped a prototype into a live venue and measured the result
- Written the eval set for an AI feature and taken it through to release
- Run a launch end to end with automated content and won a first paying venue
- Set up the delivery system in Jira, with a roadmap, a feedback loop and rituals the team keeps without being chased
The role offers:
- Direct work with the Head of Product Engineering & AI and the Managing Director on the products that will shape the company
- Products in the hands of real venues within weeks, across more than 1,400 venues in Australia and New Zealand
- The latest AI tools and the freedom to use them, with a fast learning curve while AI product management is being defined
- A competitive salary and a path to Senior Product Manager, reviewed after 12 months against the outcomes in this role
&L
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