Role details
Shape the next generation of an in-house AI system built for women's health, $180k plus equity, Sydney or Melbourne.
You'll work directly with the founders and engineering team to advance AI capability that's already in production. The core infrastructure is there: longitudinal memory, RAG, evaluation tooling, human-in-the-loop systems and internal training frameworks. Your job is to take it further.
The role sits across AI engineering and product engineering. You'll be thinking about how the underlying systems work and how they translate into something genuinely useful for the people using it.
The team works hybrid, three days in the office across Sydney or Melbourne. The AI infrastructure has been built in-house from the ground up, so you won't be stitching together third-party APIs and calling it done. There's real depth here to work with.
This is an early-stage team post a $4m raise, which means ambiguity is part of the deal. Problems won't always be well-defined when they land with you. What you get in return is significant ownership over the direction of the AI product, a 0.5 to 1% equity stake, and a genuine path to leading the AI function as the team scales through Series A and beyond.
What You'll Do
- Advance longitudinal memory, context management and RAG systems already in production.
- Build and refine LLM evaluation frameworks, fine-tuning pipelines and model orchestration across structured and unstructured health data.
- Work across conversational and voice AI, human-in-the-loop systems and emerging AI tooling as the product evolves.
- Translate AI capability into product experiences that work for real users, working closely with founders and domain experts.
What You'll Need
- Hands-on experience building and shipping AI or LLM-powered products into production.
- Solid grounding in RAG, memory systems, evals, LLM orchestration and/or fine-tuning.
- Strong software and product engineering fundamentals.
- Experience in an early-stage startup or similarly resource-constrained environment where you've taken ambiguous problems through to production.
About the Company
They're an AI-native women's health startup that has built and launched their product in-house. The platform aggregates health data across symptoms, medications, wearables and medical history to surface personalised insights for users. Post seed raise, the team is growing.
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