Australia, USA
Software Engineer, AI/ML
We’re hiring an ambitious AI engineer who wants to collaborate with PhD chemists on deep technical problems, and ship real product from day one. You’ll work directly with the founders and a team of engineers and scientists on vertical-specific AI challenges in one of the world’s most important industries.
This is one of the most interesting applied AI problems out there. Chemical data is genuinely hard: sparse, unstructured, technically dense, and full of edge cases where "close enough" isn't good enough. Retrieval alone doesn't cut it — the system needs to reason about what it's retrieved, handle ambiguity, and know when it's wrong. If you've been looking for a place where AI engineering is the product, not a feature bolted onto one, this is it.
Responsibilities
Design and ship agentic workflows, retrieval systems, and LLM features that run in production
Build the evals, tracing, and guardrails that make AI features reliable enough for enterprise customers
Work across the stack when needed — you'll spend most of your time in Python, but you'll touch the TypeScript codebase too
Turn messy, ambiguous requirements (sometimes literally chemical spec sheets) into clear, buildable systems
Keep the bar high on code quality, testing, and reliability — we're building software enterprises will run their business on
Drive timelines and keep things moving, including pushing back when scope is wrong
Personal attributes
This role is perfect for someone who's been building with LLMs hands-on, is energized by green-field problems, and cares as much about whether the system actually works in production as whether the demo looks good.
You've shipped LLM features to real users and have scars to show for it — you know the difference between a prompt that works on five examples and one that works on five thousand
You take evals seriously and have opinions about how to measure AI systems
You take ownership and push for excellence — you're the kind of person who notices the thing that's broken and fixes it, even when it's not "your" code
You don't wait to be told what to do
You're comfortable figuring things out with limited resources and imperfect information
You adapt fast when priorities change (and they will, especially in AI)
You're always improving your craft — you read papers, you tinker, you have opinions about tools and models
Technical requirements
Python, LLM tooling, agent frameworks, vector stores, eval pipelines.
TypeScript, NestJS / Express, Next.js, React, PostgreSQL for the product surfaces you'll integrate with.
Bonus points for AWS and CI/CD (GitHub Actions, CDK).
We care less about which specific tools you've used and more about how quickly you can get productive in a new one — the AI stack changes every six months anyway.
What you'll get
Builder culture. You'll have high agency and make product decisions constantly. In the age of AI, taste and judgment are the most valuable skills an engineer can have — we want people who already think this way and want to sharpen it further.
Competitive pay. Benchmarked to scale-up comp, plus a meaningful equity stake. You're an owner.
On the technical frontier. We're figuring out what AI-first software looks like for an industry that's never had modern tooling. The problems are genuinely hard: the UI/UX, data models, and agent capabilities for this space don't exist yet. You're not re-implementing something that already works elsewhere — you're inventing it.
Remote-first, AEST-anchored. We're distributed, but our core collaboration hours are Sydney time. We'll host you in Sydney for onboarding so you can meet the team in person.
No-nonsense recruitment. Informal chats with the founders and a technical conversation with the team. No LeetCode, no take-home busywork — we want to see how you actually think and build.
