Automation & AI Engineer

Founded in New Zealand in 2017, Timescapes is a visual progress tracking solution for complex construction projects. Our mission is to simplify construction through shared visibility. Customers love Timescapes because it helps them stay on schedule, validate construction claims and communicate progress more effectively.

We’re a rapidly growing company, and are used by some of the largest construction firms across Australia, Canada, New Zealand and the United States.

The Role

We're hiring a hands-on builder to lead AI and data across Timescapes: someone who finds the highest-leverage problems in the business and solves them with agentic AI, automation and better data.

You will work across every team at Timescapes, understand how work actually flows, and then build and streamline the workflows. Some of that is agentic AI but plenty of the time the right answer is a simple automation, fixing the process underneath, or removing a step nobody needed. 

This is an individual contributor role. You will scope the work, build it yourself where that is fastest, and bring in vendors or contractors where that makes more sense.

Location: Auckland, New Zealand. Hybrid, in-office.

Reporting to: Co-founder and Chief Technology Officer, moving to the Chief Operating Officer in time. 

Scope: Internal-facing, you are improving how Timescapes runs. AI inside our product is owned by a separate team, and building customer-facing AI features is not this job.

Our stack: HubSpot, Odoo, Chargebee, Mixpanel, n8n, Superset, MotherDuck and our own platform, plus the usual assortment of bolt-ons.

What You'll Be Doing

Finding and Framing the Work

• Finding the work: Partner with Sales, Marketing, Customer Success, Service Delivery, Field Service, Finance and Product to find where the real friction is, and focus on the problems with genuine payoff. The best opportunities may not necessarily arrive as requests. 
• New ways of operating: Track what is newly possible in AI and automation, evaluate the tools worth our attention, and work out what they change about how we run. Some of the biggest wins will be doing something differently, not doing the current thing faster.
• Process before automation: Map how work actually happens to deliver value to our customers, including the undocumented parts, and deeply understand the value flow before automating it.

Building and Shipping

• Build and deploy: Agentic AI workflows, automations and internal tools, particularly ones spanning multiple systems or functions. Measure outcomes, iterate, retire what is not effective. 
• Keeping it running: Take ongoing ownership of the systems and automations you build, keeping them reliable and maintainable rather than handing them off and moving on.