Senior LLMOps Engineer
Heidi Health · Melbourne · AU
Posted 60+ days ago
Software Engineering
Hybrid
Not yet analysed
Demand88
Career growth85
Healthcare fit20
Remote potential70
5-year outlook
Senior LLMOps engineers at AI startups typically command high six-figure salaries, with strong growth potential as healthcare AI adoption expands. Exact figures depend on location and equity, but the trajectory is favorable.
Clinical license
Not required
Applicant reach
broad
Seniority
senior
Employment type
full-time
Date found
2026-08-26
Intelligence details
Why this is worth applying to
Clinicians with a strong software engineering background and LLMOps experience should consider this role for its direct impact on healthcare AI. Most clinicians without deep technical expertise will find it inaccessible, but those with the skills can leverage their clinical insight to improve model feedback loops.
Who should apply
Physicians, nurses, or allied health professionals who have transitioned into software engineering, particularly with 2-3 years of LLMOps or MLOps experience, and who want to apply their clinical knowledge to AI operations.
CV angle
Emphasize any clinical experience as domain expertise that informs understanding of clinician feedback and patient session context. Highlight engineering achievements in observability, tracing, and model deployment, and frame clinical background as a differentiator for interpreting user signals.
Skills to highlight
- LLMOps
- Model observability
- Distributed tracing
- Evaluation pipelines
- Feedback loop design
- Python
- Data engineering
- Incident management
Role summary
Senior LLMOps Engineer at Heidi Health, responsible for building the operational layer around production AI models: deployment health dashboards, session-to-model lineage, feedback flywheels, and per-model unit economics. This is a hands-on engineering role in a fast-growing healthcare AI company.
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