Job Opportunities API

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. Key responsibilities 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. Requirements 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 evalua