AI Product Engineer

Triskele Labs; Melbourne; On-site; AUD 150,000 - 190,000; Full time

Job summary

Triskele Labs in Melbourne seeks an AI Product Engineer to design, scope, direct, review, integrate, and ship software using frontier AI coding tools. You will manage a portfolio of existing internal and client-facing products and collaborate with the CTO and DevOps Architect to evolve them.

This role emphasizes judgement, enthusiasm, and outcome ownership over typing speed, with a focus on secure, reliable software and strong engineering discipline.

Qualifications

• Experience designing and shipping production software end to end.
• Strong software engineering fundamentals: architecture, data modelling, security.

Responsibilities

• Design, scope, direct, review, integrate, and ship software using frontier AI tooling.
• Inherit and extend a portfolio of internal and client-facing products.
• Identify opportunities for new internal tools and client-facing products.
• Collaborate with CTO, DevOps Architect, and AI platform team on infrastructure and AI services.

Skills

AI tooling

Engineering judgement

Product instincts

Tools

Git-based workflows

CI/CD pipelines

APIs

Job description

Triskele Labs is a large-scale sovereign Australian cybersecurity provider. We deliver Managed Detection and Response (MDR), Digital Forensics and Incident Response (DFIR), offensive security, and Governance, Risk and Compliance (GRC) services to some of the most regulated and high-value organisations in Australia, across financial services, government, education, healthcare, and critical infrastructure.

Engineering excellence and operational discipline are core to how we win and keep clients. We invest in modern tooling, automation, and AI capability that allows a small, high-leverage engineering team to ship products and capability that would normally require a much larger headcount.

About the Role

The AI Product Engineer is a recent and strategic role at Triskele Labs. After recent success hiring into this capability, Triskele Labs is expanding the team. You will report to the DevOps Architect and work alongside the AI DevOps Engineer and other AI Product Engineers. This is an AI-native role. You will live inside frontier AI coding tools as your primary working environment. You are not expected to write code by hand. You are expected to design, scope, direct, review, integrate, and ship software at a pace and quality that would not be possible without AI as your engineering surface. We are hiring for judgement, enthusiasm, passion and outcome ownership, not for typing speed. You will take on a portfolio of existing internal and client-facing products and continue to build them out, including new products still in the design stage. Products may be internal-facing, or may support our delivery of services to clients. This role demands strong product instincts, sharp engineering judgement, and the discipline to operate AI tooling at a professional standard. Triskele Labs is a fast-moving environment where individuals are trusted to make calls, ship, and own what they build.

Responsibilities

Product Engineering through AI Use frontier AI coding tools as your primary engineering environment to design, build, test, and ship software products. Operate these tools at a professional standard, including planning, decomposition, prompt and context engineering, evaluation, code review, and verification of every change before it ships. Own quality, security, performance, and maintainability of everything that goes to production, regardless of how it was authored. Stay at the leading edge of frontier AI coding tools and adjust working practices as the capability evolves.

Taking on Existing Products

Inherit and extend a portfolio of existing internal and client-facing products built on modern PaaS, managed backend, and Git-based platforms. Work with the CTO and the DevOps team to understand current architecture, technical debt, and roadmap for each product. Improve reliability, security, observability, and user experience of inherited products without losing pace on new delivery.

Identifying and Building New Products

Identify opportunities for new internal tools that create operational leverage for delivery, commercial, and corporate teams. Identify opportunities for new client-facing or commercial products that strengthen the Triskele Labs offering. Propose, scope, and prototype new products with the CTO and DevOps Architect, and take them through to production where the business case supports it. Drive products end to end: discovery, design, build, launch, iteration, and sunset where appropriate.

Working Across the Business

Partner with the DevOps and AI platform engineering team for infrastructure, hosting, AI services, and shared platform capability. Engage directly with internal stakeholders across SOC, DFIR, GRC, Commercial, and Corporate to understand needs and validate solutions. Engage with clients where required to support, demonstrate, and improve client-facing products.

Engineering Discipline

Work within the Triskele Labs Secure Software Development Lifecycle, including its project tiering, mandated toolchain and workflow, data boundaries, and release and promotion gates. Compliance is a condition of shipping, not a review afterthought. Apply strong software engineering fundamentals to everything you ship: clean architecture, sensible abstractions, sound data modelling, secure by default patterns, and pragmatic testing. Use modern Git-based source control workflows, code review practices, and CI/CD pipelines. Build with security, privacy, and data classification front of mind, given the regulated nature of our client base. Document architecture, decisions, and runbooks so products can be supported, extended, and handed over. Demonstrated experience shipping production software products end to end, ideally across both internal tools and client-facing products. Strong working fluency with frontier AI coding tools as a primary engineering environment, and a clear, articulate point of view on how to use them well. Strong software engineering fundamentals: architecture, data modelling, APIs, testing, security, an