Jobs in Sydney, Australia

About the role

This role sits in the model team, the researchers and engineers who train, deploy, and own the AI models behind every Heidi product. Those models run at serious scale; what they need now is a serious operational layer around them. You'll build it: full visibility into every deployment, a feedback flywheel that turns real clinician signals into better models, and per-model unit economics that tell us which models pay their way. We're looking for someone who has already built this at an AI company operating at or beyond our maturity, and can bring that playbook to Heidi. It's a hands-on senior engineering role: you'll design the data models, build the pipelines, dashboards, and agents, and own them in production.

What you'll bring

• You've spent the last 2–3 years hands-on in an LLMOps role, building the observability, tracing, evaluation, and feedback systems around production LLMs and owning them through real incidents.
• That experience comes from an AI company operating at or ahead of Heidi's maturity, most likely in the US or China, where LLMOps practice runs deepest.
• You know what great looks like, and you can build it here.
• Proven ability to ship the systems this role owns: monitoring and alerting (Datadog or similar), distributed tracing across multi-step LLM pipelines, and session and event data models that hold up at scale.
• Experience building with LLMs, not just operating them.
• You can put an agent to work triaging feedback and matching tickets to sessions.
• Comfort joining cost and revenue data into per-model unit economics that leadership can act on.
• Senior-level ownership: you take an ambiguous mandate, design the system, and run it in production.
• No PhD required
• we care about what you've shipped.
• A broader engineering foundation before LLMOps: backend, data platform, or ML infrastructure.
• We're hiring senior, and range helps.

Benefits

Locations