AI & Automation Prototyping Engineer

Southern Cross Health Society; Auckland; On-site; NZD 120,000 - 180,000; Full time

Benefits offered by this job

Five days of wellbeing leave per year

Health insurance for you and immediate

Life insurance & discounts on pet/trav

Extra parental leave benefits

Wellbeing programme

Flexi leave for study/volunteering

Annual volunteer day

Job summary

Southern Cross Health Society is expanding its Auckland-based Data & AI team to prototype and test AI-driven solutions that scale across the business. The role blends coding with business conversations to rapidly validate what is technically viable and what delivers measurable value.

You’ll build AI agents, automation workflows and integrations, then hand off proven approaches for embedding at scale. Collaboration with analysts and engineers is essential to ship real results.

Qualifications

• Experience with generative AI tools and modern LLM-based systems.
• Experience building integrations via APIs and webhooks.
• Strong background in AI, ML, software or analytics engineering.

Responsibilities

• Build and iterate AI-driven prototypes and automation workflows.
• Experiment with generative AI tools, agent frameworks and orchestration platforms.
• Connect APIs, SaaS tools and data systems to test workflows.
• Turn ambiguous business ideas into small, testable technical experiments.
• Work with analysts, engineers and business teams to validate concepts quickly.
• Document outcomes and what’s worth taking further.
• Demonstrate working prototypes to stakeholders to inform decisions.

Skills

Generative AI

API Integrations

LLM Systems

Communication

Hands-on Coding

Tools

APIs

Automation Platforms

Job description

Southern Cross Health Society is expanding its Auckland-based Data & AI team to prototype and test AI-driven solutions that scale across the business. The role blends coding with business conversations to rapidly validate what is technically viable and what delivers measurable value.

You’ll build AI agents, automation workflows and integrations, then hand off proven approaches for embedding at scale. Collaboration with analysts and engineers is essential to ship real results.