What we’re building, and where you fit.
Supahuman builds AI operating systems for complex, regulated industries. Our flagship product, VETos, handles the work that eats up the vocational education sector: compliance mapping, assessment design, training material generation, quality assurance and a whole lot more. Work that's been slow, manual, and dependent on scarce specialists — we're turning it into something that can be done in hours instead of weeks. We're expanding into Australia now, and VETos is where we're investing.
We don't build for a faceless market. VETos gets built with the sector — alongside RTOs, TAFEs, PTEs, compliance specialists, and instructional designers, in the work itself. That shapes who thrives here.
You're the senior engineer leading delivery in one of our co-build pods: internal engineers paired with external subject-matter experts, shaping VETos alongside the people who use it. You set the technical direction and pace for the pod, and own features end to end — from the first investigation to the deploy, not a slice handed to you on a ticket. You direct AI coding agents to move fast, then bring the product judgment, technical taste, and rigour that decides whether what they produce is actually good. Investigate, scope, prototype, validate, build, deploy. The loop is yours.
“If AI does the heavy lifting, smart people get to do the thinking. That's the thesis the product has to live up to.”
Why this role is worth your time.
Own features end to end
From the first investigation to the deploy. You hold the whole loop, not a slice on a ticket. Ownership here isn't reserved for leaders or handed out slowly over years — it's the default from day one: real scope, real decisions, and the room to run with them.
Build on the agentic frontier
A real mandate to push AI coding tools — shared agent toolkits, SDLC automation, context and quality management. The reusable agents, prompts and automation you build compound, lifting the whole pod's output, not just your own.
Lead your pod's delivery
You set the technical direction and pace for your co-build team — the person they and the customer look to for how the work gets delivered.
In the sector, not on the edges
You're in the pod, in the conversations, close enough to the sector to see your work land. We co-build with VET providers, not for them — the things you ship are influenced by real users from the start, and you get to watch them make a difference rather than hearing about it secondhand through a tracker.
Never the same week twice
Build cutting-edge AI features — coaching, assessment, and more — to modernise a legacy sector, across customers and in NZ and AU. You don't need to arrive a vocational education expert: you'll get the time and access to become one, learning the domain alongside the people who live it every day.
The scope is broad by design.
You take features from a blank page to live in market — in any given week you might be deep in a customer's workflow, prototyping a direction, and shipping to production.
Own the loop, end to end
- Investigate — get into the real problem with SMEs and customers; understand the workflow before you write a line.
- Scope — define the solution and the trade-offs; generate and refine requirements with AI, and know when output is good enough.
- Prototype — stand up testable versions fast; prove the direction before committing to a full build.
- Validate — put it in front of SMEs and customers; course-correct on real feedback, not assumptions.
- Build — direct AI coding agents to do the heavy lifting; bring the taste and rigour that makes the output production-grade.
- Deploy — ship to market and own quality through release; feed the patterns back into the core product.
Agentic development
- Direct LLM coding agents (Claude Code, Cursor, Copilot) as your primary tool.
- Build and curate reusable agents, prompts, and automation.
- Automate more of the SDLC — scoping, testing, reviewing, deploying.
- Critically evaluate AI output and course-correct.
Product & UX judgment
- Make confident calls on scope, trade-offs, and direction.
- Produce UX flows and interaction specs rapidly with AI-assisted tools.
- Champion rapid prototyping over over-specifying.
- Bring product thinking into engineering decisions, not just technical thinking.
Quality, in the pod
- Hold quality standards: correctness, UX, code, agent-output review.
- Manage technical debt on what you touch — velocity with health.
- Collaborate with external SMEs; keep knowledge documented, not in heads.
- Share agentic practices across the team — docs, patterns, mentoring peers.
Be Brave. Be Hungry. Be Human.
We live by three values — and we’re searching for someone who embodies them and puts customers at the centre of their work.
Calm and direct. You make tough technical and product calls and carry a client or SME through uncertainty. You bridge technical and non-technical worlds without hiding behind complexity, and challenge assumptions to build trust, not to score points.
You don't wait to be asked. You see opportunities and act — sharpening a prompt, improving a CI pipeline, building a reusable agent. You're curious about the AI ecosystem and know how to separate useful from hype.
You work with others, not around them. Generous with feedback, inclusive in problem-solving. You handle hard conversations with honesty and respect. People trust you because you show up, listen, and make space for different perspectives.
What you’ll bring.
Engineering foundations
- 4+ years of senior-level engineering.
- Strong hands-on skills across technologies such as JavaScript, TypeScript, Python, Next.js, React, AWS, Google Cloud, Azure, SQL and NoSQL.
Core Gen AI technologies & concepts
- Model SDKs (e.g. OpenAI, Anthropic, Gemini) and agent frameworks (e.g. LangChain, ADK).
- Vector DBs & RAG (e.g. pgvector, Pinecone), MCP, and prompt & context engineering.
- AI safety & guardrails; cost, accuracy and latency tradeoffs.
Agentic development
- Directing LLM-powered coding agents (Claude Code, Cursor, Copilot).
- Building custom agents, prompts, and automation workflows.
- Setting standards for agent quality, governance, and safe automation.
- Staying current with AI models and making pragmatic adoption calls.
Product & UX — AI-assisted
- Generating and refining requirements with AI — knowing when output is good enough.
- Producing UX flows and interaction specs rapidly with AI-assisted design tools.
- Leading rapid prototyping — testable versions quickly, not over-specifying.
- Making confident product calls on scope, trade-offs, and direction.
End-to-end ownership
- Owning features from investigation to deploy, in co-build with SMEs and customers.
- Holding senior client relationships through multi-month engagements.
- Managing technical debt and balancing velocity with long-term health.
- Building systems that make team knowledge durable and accessible.
A note on this role
- It sits at an unusual intersection, and we don't expect a perfect match. Deep technical craft, product thinking, and agentic AI — plus the appetite to own a feature from the first conversation to live in market. We're looking for strong foundations, genuine curiosity about AI and the sector, and the drive to build something new.
What good looks like, twelve months in.
Sound like you?
Tell us why you’re a great fit for the Lead Product Engineer role — send your CV and a short note to jobs@supahuman.ai.
Apply — jobs@supahuman.aiSupahuman is an equal-opportunity employer. We hire for potential and value diverse perspectives.