About this role
About Valocity
Valocity is a New Zealand-founded property technology company. Our cloud platform connects valuers, lenders, brokers, insurers and real estate professionals across the valuation and lending lifecycle, and is used every day by four of New Zealand’s five largest banks. We operate across New Zealand, Australia, India and the UAE, with products including Nexus, Valocity Connect and our automated valuation and data services.
Our current R&D focus is applying AI to how we build, test, release and assure software. Build with AI is the programme behind that work, and our interns work on it directly.
About the role
This is a paid, full-time summer internship for a student who wants to work as a junior engineer on real, open-ended R&D. You will join an engineering pod, contribute across our Build with AI tools, and work inside our production tooling and codebases, not a sandbox. You will have a named mentor who meets with you weekly and reviews your work.
You will go through the full cycle of commercial R&D: defining the problem, prototyping, testing against real users and real data, and deciding whether the result is good enough to use. At the end of the internship you will present your findings to engineering leadership.
Positions available in both Auckland and Wellington locations.
What you could work on
Our Build with AI tools (EngineeringIQ, ReleaseIQ and AuditIQ) apply AI across the way we build, release and assure software. Interns work across these tools rather than on a single fixed task, so the exact mix will depend on where the programme is when you join and on your strengths. The work spans areas such as:
- AI-assisted quality and release – Explore how AI can check that what we test matches what was asked for, prepare test cases and data ahead of a build, spot unintended UX changes between releases, and produce clear release evidence that testers and product owners can rely on.
- AI-assisted engineering and change verification – Work with our AI engineering peer to help define code changes and then confirm they have been implemented correctly, whether that change is to a user interface, an API contract or a database, and feed that confidence into release testing.
- AI for assurance and compliance – Investigate how AI can read the varied security and audit questions our bank and lender clients send us, connect them to the evidence we already hold, and draft accurate first responses for our compliance team to review.
- AI over property data – Apply generative AI to messy, real-world property data from multiple sources, reconciling conflicting records into a history people can trust and query in plain language.
- Modern build architecture on Azure – Help shape the platform these tools run on: containers, Kubernetes and Azure Container Apps, API gateways, infrastructure-as-code, CI/CD pipelines and observability, with a focus on making build and test environments safe and repeatable for AI-assisted delivery.
In every area the questions are open: we do not yet know the best answer, so you will prototype, measure against real data and real users, and help decide what is good enough to use.
Key responsibilities
- Design, build and test software components across the Build with AI tools, working within the pod’s sprint rhythm.
- Use AI-assisted development tools responsibly, within Valocity’s AI and security guidelines, and record where AI helped and where it did not.
- Build and deploy on Azure using our Platform 2.0 patterns, including containers, infrastructure-as-code and CI/CD pipelines.
- Design experiments and measure results (accuracy, reliability, cost, effort) against real data, releases and users.
- Work through GitHub, Jira and our CI pipelines, following code review, branching and release governance.
- Write clear documentation of approach, findings and recommendations so the team can reuse your work.
- Collaborate with engineers, testers, architects and product people across NZ, Australia and India.
- Present progress weekly to your mentor, and demo your work to stakeholders mid-way and at the end of the internship.
What you will learn
AI-assisted software engineering
How you will develop it: Use AI development tools daily to build, test and evaluate your component, documenting where AI output was trusted, adapted or rejected.
What you will be able to do: Critically evaluate AI-generated output and apply it appropriately in a production engineering context.
Cloud and platform engineering on Azure
How you will develop it: Work with Azure services, containers, infrastructure-as-code and CI/CD alongside our platform engineers.
What you will be able to do: Build and deploy a service using modern, secure, cost-aware Azure patterns.
Working in a live commercial pipeline
How you will develop it: Contribute through GitHub, Jira, CI and our compliance tooling with weekly mentor guidance.
What you will be able to do: Navigate and contribute safely to a live commercial software environment.
Communication and presentation
How you will develop it: Present progress weekly to your mentor and demo to stakeholders mid-way and at the end of the internship.
What you will be able to do: Explain technical findings clearly to technical and non-technical audiences.
Time management within an R&D plan
How you will develop it: Own a weekly work plan against the 10-week internship scope, agreeing priorities with your mentor.
What you will be able to do: Plan, prioritise and deliver a bounded piece of R&D work independently.
About you
What you will bring
- Currently studying (or recently completed) a degree in software engineering, computer science, data science or a related field.
- Solid programming foundations in at least one modern language, ideally C#/.NET, Python or TypeScript.
- Hands-on use of AI coding assistants or LLM APIs, through study, projects or personal work.
- A working understanding of Git, APIs and relational databases.
- Curiosity about open-ended problems, and the discipline to test your ideas rather than assume they work.
- Clear written and spoken communication, and comfort asking questions early.
Nice to have
- Exposure to Microsoft Azure or another cloud platform, containers (Docker, Kubernetes) or infrastructure-as-code (Bicep or Terraform).
- Experience with CI/CD tools such as GitHub Actions.
- Interest in test automation, prompt design, retrieval-augmented generation, agent tooling or Model Context Protocol (MCP).
- Experience with data wrangling, NLP or working with messy, real-world data sets.
- Awareness of security and compliance frameworks such as SOC 2 or ISO 27001.
Eligibility
This internship is supported by the New Zealand Government’s R&D Experience Grant, administered by MBIE. To be eligible you must:
- Be studying, or have studied, at a New Zealand tertiary institution (study completed overseas is not eligible).
- Be studying at NZQA level 6 to 10, or have completed study with your last semester closing less than 12 months ago.
- Be studying science, technology, engineering, design or business.
- Be legally permitted to work in New Zealand.
- Not have been previously employed by Valocity, except in part-time or temporary work.
- Not have already completed two R&D Experience Grant internships with Valocity.
- Be able to work full-time and on site in Auckland or Wellington for the 10-week term.
You will need to provide evidence of enrolment or study from your institution.
How to apply
Send your CV, academic transcript and a short cover letter telling us which areas of work interest you most, why, and whether you are applying for Auckland or Wellington. A link to a GitHub repo or something you have built, especially with AI, is a strong plus.
