Full job description

About Mutinex

At Mutinex, we believe marketing deserves to be treated as a performance discipline — not a cost centre. We're building the growth decision engine that replaces slow, conflicted measurement with fast, independent, AI-powered intelligence. Trusted by brands like Hershey, Samsung, and Domino's, our platform empowers marketers to make confident, data-driven decisions that drive real business growth. We're an Australian-born, globally scaling B2B SaaS company — and we're just getting started.

Hybrid across Sydney, Melbourne, and New York. We highly value communication, open-mindedness, and a culture of feedback.

How We Work

The way software gets built is changing. We're changing with it — deliberately and quickly, but we're not done yet.

Our direction is clear. The hard work of engineering is shifting from implementation to planning, orchestration, and judgment. We want engineers who direct AI agents, review output, and focus their energy on the decisions that matter — architecture, design, product thinking. Writing code by hand is becoming the exception, not the default.

Here's where we are today: we use Claude Code as our primary AI development tool. We've built Forge — our internal tooling layer with shared skills, agents, and hooks that encode team knowledge. We run weekly AI Office Hours to pair on real problems. We track AI usage and change lead time to keep ourselves honest. Every engineer is expected to be actively building this skill.

Here's where we're heading: a workflow where AI handles ideation scaffolding, task breakdowns, implementation, test generation, code review prep, and release notes — and engineers focus on the thinking that AI can't do. Problem decomposition. Architectural trade-offs. Knowing when the AI is wrong and why. We're not there yet on every team, but the engineers joining now will shape how we get there.

If this is already how you work — or it's clearly where you're headed — read on.

The Role

You'll be a technical contributor building and scaling one of our core platforms: DataOS (automating data ingestion and processing) and GrowthOS / MAITE (our customer-facing growth co-pilot). The role is full-stack and moves across both. You go wherever the highest-impact work is.

What the work looks like:

You plan features with AI before a line of code exists. You break problems into stages, prompt effectively, manage context across sessions, and direct agents to build end-to-end — from backend services to the frontend that consumes them. You review what comes back with a critical eye, and you take ownership of what ships.

Specifically:

• Plan, direct, and ship end-to-end features — from data model to user interface — using AI agents as your primary development tool.
• Build and sharpen your judgment about AI output — catching hallucinated APIs, incorrect state assumptions, security patterns that look right but aren't, tests that pass but don't test what they should. We expect you to have this instinct already, and we invest in making it sharper.
• Contribute to the platform's architecture, and bring a view on why systems should be designed the way they are — that judgement is what makes AI direction sharp.
• Build and maintain guardrails — testing strategies, verification discipline, and review habits that keep pace with shipping velocity.
• Collaborate across product, design, data science, and engineering — because when building is fast, judgment about what to build matters more than ever.

What We're Looking For

We're hiring for how you work with AI and for the judgement that comes from having shipped and run real systems. Some of you will bring more production depth, some more AI-native fluency — we want both, and we expect real evidence of at least one. What's non-negotiable is that you're already on the train and accelerating.

What Matters Most

• Evidence over credentials. Show us what you've built, not where you studied.
• Judgement about what you ship. We'd rather see someone who has owned a system in production and rebuilt the way they work with agents than someone with only one half of that.
• Product sense. You think about why something should be built, not just how.
• Ownership in production. You've owned features end to end, and you've been on the hook when they broke.
• Intellectual honesty. You know what you don't know. You ask for help. You share what you learn.

What We Invest In You

You bring AI-native fluency and engineering judgement. We invest in pushing both further than you'd get on your own.

Weekly AI Office Hours. 1:1 pairing sessions on real problems — bring a feature you're working on and we'll work through it together. Up to 4 hours every week pairing with the rest of the team.

Forge — our internal AI tooling layer. Shared skills, agents, MCP servers, and hooks built by the team, for the team. You'll benefit from what others have built and contribute your own. The engineers who lean in shape how everyone works.

Cool-down time for skill-building. Protected time built into our rhythm for experimentation, learning, and going deep on something that interests you.

• Working alongside engineers who've built production systems at scale, on the shared problem of turning AI velocity into AI quality. You'll sharpen others as much as they sharpen you.

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