AI Automation Lead

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.
Main Purpose of Position 

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.

The role has two connected mandates:

AI transformation. Work directly with every team at Timescapes (Sales, Marketing, Customer Success, Finance, Operations, Product) to identify where agentic AI genuinely helps, then build, ship and maintain real solutions that people actually adopt.

Data & reporting. Our data currently lives across a number of systems (CRM, product analytics, finance, support and more). You'll design and build a unified reporting system, moving the whole company toward one consistent view of performance. Good data is also the foundation that makes the AI work possible, which is why these two mandates belong in one role.

This is an individual contributor role. You'll scope the work, build it yourself where that's fastest, and bring in vendors or contractors where that makes more sense. You'll be reporting to the CTO initially, in time moving to Operations.

• Partner with leaders and teams across the company to identify where AI and automation can help, and focus effort on the opportunities with real payoff.
• Work with subject-matter experts to map existing processes and workflows, including the undocumented ones, and identify what's broken or inconsistent. Fix the process first: automating a bad one just makes the mess move faster.
• Build and deploy agentic AI workflows, tools and automations that measurably improve how we work, then make sure they stick: measure outcomes, iterate, and retire what isn't earning its keep.
• Design and build our reporting platform: build ELT pipelines from our core systems, and model the data so it's reliable, well-documented and easy to build on.
• Improve and consolidate company reporting: our current reporting is solid in some areas and lacking in others. Strengthen the gaps, consolidate what's scattered, and move us toward a single, trusted view of company performance.
• Manage vendors and contractors where buying beats building, and own those relationships end to end.
• Lead by example as the most active AI practitioner in the company: run enablement sessions, create practical playbooks, and upskill teams so the capability spreads beyond you.
• Establish sensible guardrails for responsible AI and data use: privacy, security, appropriate use, and transparency about where AI is involved.
• Stay close to the frontier. Evaluate new tools, models and approaches, and translate what actually matters for a company our size.
• Take ongoing ownership of the systems and automations you build, keeping them reliable and maintainable rather than handing them off and moving on.
• Keep running costs under control and visible to the teams that use each solution, so they can make an informed call on whether the costs are justified.

• You've done this work before and can show it. We care far more about what you've shipped than the exact titles you've held.
• Hands-on, current experience building with LLMs and agentic AI: workflow builders, automation platforms, agent frameworks, and the judgement to know when a simple script beats an agent.
• Strong data engineering fundamentals: expert SQL, and hands-on experience across the modern data stack (warehouse platforms, ELT tooling, data modelling, BI layers). Breadth matters here: we want someone who can evaluate the options and recommend what fits Timescapes, rather than defaulting to whatever they've used before.
• Experience building reporting and BI that non-technical teams actually use, and defining metrics with the people who own them.
• Comfortable working directly with commercial systems and their APIs: CRMs, product analytics, finance and support tools.
• Experience scoping and managing external vendors or contractors, and making sound build-vs-buy calls.
• A practical point of view on responsible AI: data privacy, security and appropriate use, applied in practice rather than in theory.
• Comfortable with ambiguity. You can hold a company-wide view while executing in the detail, and when there's no playbook, you write it.

• 5+ years across data, analytics engineering, automation or related roles, with recent and substantial hands-on AI work.
• A portfolio of things you've built: automations, agents, data platforms, reporting systems. We'll ask you to walk us through them.
• Experience in a fast-moving SaaS or startup environment where you owned outcomes end to end.
• A natural enabler. You don't hoard knowledge, you multiply it, including with people who are sceptical or overwhelmed by AI.
• Strong communicator in writing and in person, comfortable working with everyone from engineers to finance to sales.

Our team tells us what they value most: the people, the product, the trust, and the opportunity to do work that actually matters. We have built that culture deliberately and we look for it in every hire we make.

If you are looking for a place where your work ships into the real world, where the team is small enough that your contributions matter, and where the mission is clear, we would love to hear from you.

• Timescapes contributes 5% to Kiwisaver for all eligible employees
• Southern Cross Health Insurance
• EAP via Clearhead
• Enhanced Paid Parental Leave