Product Platform Verification Engineer - Smartly at Datacom

Auckland, Auckland, New Zealand -

Full Time

Start Date

Immediate

Expiry Date

25 Aug, 26

Salary

0.0

Posted On

27 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Verification Infrastructure, Automated Frameworks, CI/CD Pipelines, C#/.NET, Python, TypeScript, API Verification, Web Application Testing, Data Layer Verification, Performance Testing, Security Testing, Functional Testing, Integration Testing, AI-Assisted Verification, Architectural Design, Technical Writing

Industry

IT Services and IT Consulting

Description

Product Platform Verification Engineer Remote in New Zealand, The Smartly Platforms and Architecture Team are looking for a Product Platform Verification Engineer to own the frameworks, pipelines, and guardrails that give the engineering org confidence in what it ships. How might we give every engineering team the confidence to ship faster, even as more code is generated by agents? How might we catch problems at the cheapest place in the delivery cycle, by verifying inputs as rigorously as outputs? How might we make verification a paved road our engineers actively want to use? Our Why At Smartly we care deeply about quality — we pay people. Getting it wrong means people don't get paid correctly, or at all, and we take that very seriously (so seriously that we even pay ourselves with that same software). At the same time, traditional testing roles are changing. More code than ever is being generated by agents. The quantity of that code is increasing, and the cost of creating it is decreasing. How do we guarantee quality in that world? I don't believe it's enough anymore to simply test output code or functionality, because it's trivial to change the inputs that generated that output. Instead we have to test the inputs as rigorously as the output, and we have to test both more deeply than before. It's easy to demonstrate that unit, integration, end-to-end, performance, security, or regression tests pass. They are binary. But we apply more than binary tests when building products. Does the output implement our architecture design faithfully? Does it implement logging, observability, and other Smartly engineering standards correctly? Does it follow our conventions? Does it implement the solution design correctly? How might we test for taste? How might we test for adherence to design principles? Over time we will generate more code than we write, and humans will read fewer lines of code while focusing more on high risk code paths. We need someone who has thought about these questions — someone who can build the quality automation and pipelines that will keep us safe as we move faster than ever. About the Role (your why) Verification at Smartly is broader than testing. It isn't a separate gate bolted on at the end — it's part of how work flows, from spec to ship. You own the verification frameworks, pipelines, and guardrails that engineering teams across the company consume as self-service: functional, integration, security, performance. Engineers writing the code own their tests; you own the frameworks those tests run in and the gates they flow through. What you'll do No two weeks are the same, but here's the rough shape. Building! You will build a lot. On Monday that might be input verification - pairing with a product person to work out how we verify intangible qualities of the product. Tuesday might see you assessing the quality and coverage of our current automation harnesses. Wednesday might be about filling the gaps you found on Tuesday. On Thursday you might decide that there is a better way of assessing adherence to architectural principles, and so you might run an experiment on that. Friday is for learning. Writing — verification approach docs, failure-mode analyses, coverage and gap analyses, agentic prompts that the whole team will use. Coding on the frameworks and pipeline tooling you own. Time with the team on the shared AI tooling that makes the whole engineering org faster. We write things down. Decisions, designs, tradeoffs, and post-incident learnings live on the page. It's how we think, how we align, and how we work async. It is vital that you believe in writing as we do. Writing is not a chore to be done at the end of your work in this team. Writing is a forcing function for thinking and for clarity. You will only succeed here if you love writing as we do. Focus time is non-negotiable. We protect the calendar for deep work. Meetings have a purpose or they don't happen. We tend to focus in the morning and meet in the afternoons. Async standups by default, 3 o'clock Smoko twice a week where work talk is banned and we connect as humans. What working with us is like Our team are full of thoughtful people who want to help others. We believe in respecting focus time and acting with remote-first intentionality. We believe in strategic laziness - why would I keep doing this manual stuff when a machine can do it for me? The team are pragmatic and want to make choices that favour technical purity, AND we acknowledge that sometimes that's not the right thing for the business and for our colleagues. When you join this team, your standards will become team standards. Your judgement, vision, taste, agency and ownership will make everyone around you faster. What you'll bring You build verification infrastructure. You don't execute manual scripts. You've designed and maintained automated frameworks that other engineers use, and you have opinions about what makes a framework adoptable versus what makes it shelfware. You can verify web applications, APIs, and data layers across functional and non-functional requirements. You've integrated verification into CI/CD pipelines and you know how to diagnose weak pipeline signals when they show up. You're deeply comfortable doing demanding engineering work in the context of verification. You can read and write at least one of C#/dotnet, python, or typescript fluently — and read across all three. You'll be building infrastructure that hooks into our CI/CD pipelines, our monolith, our microservices, and the agentic environments we run. Our verification stack is light today and the target state is yours to help shape. You need to be comfortable writing code that other engineers depend on, debugging weak pipeline signals, and making decisions about which verification approach fits which problem. You need to thrive in that space, and help others feel at home there too. You have judgement, taste, vision, and context. The four things AI can't replace. You can look at AI-generated tests and tell the difference between coverage and the appearance of coverage. You think about verification holistically: inputs as well as outputs, the spec as well as the code, architecture and standards as well as functional correctness. You're excited about what AI changes in engineering. As more code is generated by agents, verification processes have to verify inputs as rigorously as outputs and go beyond pass/fail. Scaffolding generation, gap analysis, agent-driven exploration of failure modes, complete environments for agents to validate their own work — this is one of the most interesting frontiers in our craft right now, and you want to be on it. If this is you I'd love to hear from you. Please apply. If parts of this resonate but you're worried you don't tick every box — please apply anyway. The traits I'm looking for — judgement, taste, vision, context, agency, ownership — don't come from a particular degree, background, or career path. Smartly is committed to building a team that reflects Aotearoa New Zealand, and I'd particularly like to hear from women, Māori, Pasifika, takatāpui, disabled and neurodivergent engineers, and anyone who took a non-linear path into the work. If you need any adjustments to be at your best in the conversation or beyond, tell me. When you write, tell me about a verification framework you built that other teams actually adopted, a coverage gap you found that nobody else saw coming, or a piece of AI-assisted verification work you're proud of.

Responsibilities

Own and build the verification frameworks, pipelines, and guardrails used by engineering teams to ensure software quality. Develop automated systems to verify both inputs and outputs, focusing on architectural adherence and AI-generated code quality.