Principal Applied Scientist

At Oracle Health and AI (OHAI), we’re not just building the future of healthcare applications - we’re redefining it. Our diverse team of visionaries and innovators is at the forefront of cutting-edge AI technology, particularly Generative AI, where creativity meets precision. As pioneers in this space, we’ve consistently delivered industry-leading AI solutions, notably forthe Oracle Clinical Digital Assistant, solidifying our reputation as trusted leaders in the field.

As we scale, we’re building a new kind of role at the intersection of applied science, customer partnership, and high-velocity delivery. Our Principal Applied Scientist role is not a traditional research or model-building role - it’s a role for scientists who thrive in the field, turning real clinical workflows into working AI-powered solutions at speed. As part of this expansion, we have open positions in Australia.

The Role

The Principal Applied Scientist operates at the frontline of customer engagement and solution delivery. Where our scientists advance the core AI platform, the Principal Applied Scientist takes that platform into the real world - embedding with customers, deeply understanding their clinical and operational workflows, and rapidly building, adapting, and shipping AI solutions that create immediate value.

This role demands a rare combination: the technical depth to architect and build AI systems, the product instinct to identify what matters in a customer’s workflow, and the velocity to move from problem to prototype to production in days, not months.

Responsibilities

• Embed directly with healthcare customers and clinical teams to develop a deep, first-hand understanding of their workflows, pain points, and operational realities.

• Translate observed customer workflows into concrete AI solution designs, identifying high-impact opportunities where generative AI can deliver measurable improvement.

• Build and ship AI-powered prototypes and production solutions at high velocity, using AI-accelerated development practices to compress the cycle from insight to working software.

• Rapidly iterate on solutions based on live customer feedback, clinical validation, and real-world performance data - treating every deployment as a learning loop.

• Leverage AI coding tools, automated testing, and modern acceleration frameworks to sustain a pace of delivery that traditional development cannot match.

• Serve as the technical bridge between customer needs and OHAI’s core AI platform, feeding field insights back to the Applied Science and Engineering teams to shape the product roadmap.

• Design and execute solution architectures that are pragmatic, deployable, and robust enough for clinical environments, balancing speed with reliability.

• Develop reusable patterns, templates, and toolkits that scale successful deployments across multiple customer sites.

• Own the end-to-end delivery of customer-facing AI solutions, from initial scoping through deployment, monitoring, and handover.

• Communicate complex technical concepts clearly to clinical stakeholders, executives, and non-technical partners, building trust and alignment.

• Identify and manage risks specific to deploying AI in live healthcare settings, including data quality, integration challenges, and change management.

Qualifications and Experience

Required

• Demonstrated experience in AI-accelerated development - using LLMs, AI coding assistants, and generative AI tools as core parts of your own development workflow to dramatically increase speed and output.

• Proven ability to rapidly iterate: a track record of moving from ambiguous customer problems to working prototypes in days, not quarters.

• Strong experience working directly with customers or end users to understand workflows, gather requirements, and co-design solutions - not from a spec document, but from direct observation and partnership.

• Ability to translate complex, messy, real-world workflows into clear solution architectures and working AI applications.

• Hands-on proficiency building applications with Large Language Models (LLMs) and generative AI, including prompt engineering, retrieval-augmented generation (RAG), agent-based architectures, and API integration.

• Strong software engineering skills with the ability to write production-quality code quickly - comfort across the stack, from backend services to lightweight front-end interfaces.

• Familiarity with modern LLM frameworks and tooling (e.g., LangChain, LlamaIndex, vector stores, function calling, evaluation frameworks).

• Excellent communication and stakeholder management skills - the ability to build rapport with clinical staff, present to executives, and navigate complex organisationaldynamics.

• A bias for action and comfort with ambiguity: you default to building and testing over planning and analysing.

• Must be eligible to work in Australia without sponsorship.

Preferred Qualifications

• Experience deploying AI solutions in healthcare, clinical, or regulated environments.

• Familiarity with clinical workflows, electronic health records (EHR), or health data standards (HL7, FHIR).

• Experience with computer vision, multimodal models, or clinical NLP.

• Background in consulting, solutions engineering, customer success, or other customer-facing technical roles.

• Experience building internal tools, accelerators, or reusable deployment frameworks.

Education

• Master’s or Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field with 3-5+ years of relevant experience in applied AI, solutions engineering, or a comparable role; OR

• PhD in a related field with relevant applied experience.