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Creative Thinking Institute is building the institute, product, and governance layer behind clinician-led AI healthcare work, including Regenemm Healthcare. We are now making two senior technical appointments for the next growth phase.

This is a formal hiring release for senior builders who can help move the work from founder-led technical development into a disciplined, healthcare-grade engineering organisation.

Senior technical hiring release

Release date: 4 May 2026

We are asking for two senior roles:

  1. Chief Technology Officer / technical co-lead - a senior build-and-ship technology leader for architecture, AI systems, security, cloud, edge, clinical safety, engineering standards, and the next stage of team formation.
  2. Senior Full Stack AI Engineer - a senior implementation engineer who can ship healthcare-grade product features across frontend, backend, APIs, data, AI orchestration, evaluation, deployment, and agent-assisted engineering workflows.

These are not general expressions of interest. They are specific asks for people with real healthcare software implementation experience, strong engineering judgment, and the ability to work directly with a clinician-founder/product owner.

Before applying, please read both websites:

  • Creative Thinking Institute - parent institute, research lineage, governance posture, healthcare AI writing, and public company context.
  • Regenemm Healthcare - clinical product company, platform direction, trust material, security posture, and product context.

If one of these roles describes the contribution you can make, email bren@regenemm.com with the relevant subject line listed under the role.

Applications should be concise, evidence-based, and specific. We are more interested in what you have built, shipped, governed, secured, evaluated, or led than in generic AI enthusiasm.

Chief Technology Officer

Creative Thinking Institute / Regenemm Healthcare

Melbourne, Australia - On-site - Full-time

Release date: 4 May 2026

Current ask: Senior CTO / technical co-lead for the next growth phase.

Reporting to: Founder and CEO, Dr Brendan O'Brien - neurosurgeon, product owner, and software developer

Read before applying: Creative Thinking Institute and Regenemm Healthcare

CTA: Email bren@regenemm.com with subject line Application - CTO - Regenemm Healthcare.

About us

Regenemm Healthcare is building clinical AI infrastructure: the substrate beneath secure, auditable, clinician-facing healthcare software.

Our platform is organised around a Hub-and-Spoke architecture. The Hub governs clinical truth, provenance, consent, interoperability, orchestration, and audit. The Spokes deliver focused workflows for clinicians, patients, hospitals, home care, billing, medicolegal processes, and healthcare coordination.

We operate an internal ecosystem of approximately 30 AI agents working alongside our engineers across software development, architecture, clinical documentation, infrastructure, governance, research, and product. We are now looking for a CTO who can take that system to the next level.

This role sits at the intersection of clinical software, AI infrastructure, agentic engineering, security, cloud architecture, edge computing, and healthcare-grade governance.

The ask

You will own the technical strategy, engineering discipline, AI infrastructure, and security posture for the platform.

This is a build-and-ship CTO role, not an advisory one. You will write code, review architecture, design agent systems, make infrastructure decisions, set engineering standards, and lead the transition from founder-led technical development into a durable, disciplined engineering organisation.

Concretely, you will:

  • Define and lead the technical roadmap across Regenemm Voice, Link, Hospital Hub, Home Hub, Billing, Edge Connector, and future clinical workflow modules.
  • Design and govern the agentic engineering environment, including agent roles, tool boundaries, review loops, escalation pathways, audit, and human approval gates.
  • Lead the AI stack across LLM orchestration, RAG, embeddings, evaluation harnesses, local and edge inference, and fine-tuning where it earns its place.
  • Own AWS architecture, infrastructure-as-code, CI/CD, observability, secure networking, and deployment discipline across cloud, on-premise, and edge environments.
  • Set the bar for clinical safety, including provenance, audit trails, consent, clinician-in-the-loop review, patient-data protection, and failure-mode design.
  • Build systems that can support real healthcare workflows rather than superficial AI demonstrations.
  • Hire and lead a small, exceptional engineering team augmented by AI agents.
  • Create a technical culture based on evidence, verification, narrow implementation lanes, clear documentation, and accountable delivery.

Healthcare domain experience is non-negotiable

This role requires demonstrated healthcare domain experience.

Candidates must be able to show prior work in one or more of the following areas:

  • Healthcare, medtech, digital health, clinical software, hospital systems, or patient-facing health systems.
  • EMR/EHR workflows, FHIR, HL7, pathology/radiology/result feeds, or clinical interoperability.
  • Medical documentation, clinical workflow automation, patient communication, care coordination, or clinician-facing software.
  • Regulated health environments involving privacy, consent, audit, patient data, clinical safety, or operational governance.
  • Closely adjacent clinical technology where the candidate can clearly demonstrate healthcare implementation knowledge.

General AI experience without healthcare implementation experience is not sufficient for this role.

What we need to see

  • Demonstrable healthcare domain experience, as outlined above.
  • Production AI systems you have shipped in healthcare, medtech, digital health, regulated clinical software, or a closely adjacent healthcare domain.
  • Senior engineering or technical leadership experience, with a record of writing and reviewing code at depth.
  • Strong AWS and modern infrastructure-as-code practice, ideally including Terraform.
  • Hands-on experience with LLMs, RAG, agents, evaluation systems, AI-assisted development workflows, and production AI integration.
  • Practical understanding of edge computing, local-device inference, hybrid cloud/local architectures, and model deployment constraints.
  • Sound security, privacy, and systems engineering judgment.
  • Clear written architectural communication.
  • Ability to work directly with a clinician-founder in a fast-moving, high-accountability environment.
  • Capacity to lead engineers and AI agents without losing control of quality, security, clinical safety, or technical direction.

Strongly preferred

  • Familiarity with FHIR, HL7, EMR/EHR integration, clinical documentation, or patient-data workflows.
  • Practical experience with ISO 42001, ISO 27001, HIPAA, GDPR, SOC 2, or equivalent control frameworks.
  • Prior CTO, founding engineer, senior technical founder, principal engineer, or senior technical product leadership experience.
  • Experience with edge computing, local-device AI deployment, GPU/accelerator-aware deployment, or hybrid cloud/local architectures.
  • Experience building or governing AI-agent-assisted engineering teams.
  • Experience working in founder-led, high-ambiguity, high-accountability environments.
  • Ability to translate clinical requirements into safe, testable, auditable software systems.

Technical domains relevant to this role

You do not need to have used every tool or framework listed below. You do need enough breadth, judgment, and implementation history to lead decisions across these domains.

AI and agentic systems

  • LLM orchestration.
  • Retrieval-augmented generation.
  • Embedding pipelines.
  • Vector databases.
  • Tool and function calling.
  • AI coding agents.
  • Multi-agent engineering workflows.
  • Prompt and context engineering.
  • Evaluation harnesses.
  • Regression testing for AI quality.
  • Synthetic data workflows.
  • Fine-tuning and LoRA where appropriate.
  • Local model testing and deployment.
  • Failure-mode analysis for clinical AI outputs.

Cloud, infrastructure, and deployment

  • AWS.
  • Terraform or equivalent infrastructure-as-code.
  • Docker and containerised services.
  • ECS/ECR or equivalent deployment models.
  • GitHub Actions or equivalent CI/CD.
  • Observability, logs, metrics, and alerting.
  • Secure networking.
  • Secrets management.
  • Edge and local compute pathways.
  • Hybrid cloud/on-premise architecture.

Healthcare-grade systems

  • Provenance and lineage.
  • Consent-aware data sharing.
  • Audit trails.
  • Clinician-in-the-loop review.
  • Clinical documentation workflows.
  • Patient-data protection.
  • Interoperability.
  • Fail-closed design.
  • Security and compliance evidence.
  • Controlled release of clinical outputs.

Personal attributes

We are looking for someone who is:

  • Technically exceptional and implementation-focused.
  • Comfortable writing code and reviewing code at depth.
  • Able to distinguish production-grade AI infrastructure from impressive AI demos.
  • Clinically safety-aware.
  • Security-conscious.
  • Direct and clear in written communication.
  • Calm under ambiguity.
  • Capable of imposing engineering discipline on fast-moving AI workflows.
  • Pragmatic rather than theoretical.
  • Able to lead both humans and AI agents with clear standards.
  • Comfortable working closely with a clinician-founder/product owner.

Compensation

  • Wage: To be discussed (TBD) + super.
  • Meaningful founding-team equity in Creative Thinking Institute Pty Ltd.
  • Melbourne on-site, with pragmatic flexibility for senior candidates.
  • Standard Australian employment conditions.
  • Full work rights in Australia preferred; sponsorship may be considered for exceptional candidates.

How to apply

Email bren@regenemm.com with subject line:

Application - CTO - Regenemm Healthcare

Please include:

  1. CV or professional profile.
  2. Evidence of shipped AI systems, such as links, repositories, architecture write-ups, product screenshots, technical dossiers, implementation summaries, or private examples that can be discussed confidentially.
  3. A brief description of your healthcare domain experience, including the clinical, operational, regulatory, interoperability, or patient-data context in which you worked.
  4. A short written response of no more than 500 words to: "How would you design and govern an AI-agent-assisted engineering team building clinical AI infrastructure, and what healthcare-specific risks would you control first?"
  5. Two references who can speak directly to your implementation work.

Shortlisted candidates will be contacted directly.

Application materials will be reviewed by Dr Brendan O'Brien.

Our hiring standard

We are seeking candidates with exceptional capability and verifiable implementation history.

We are particularly interested in people who can demonstrate:

  • Real healthcare software delivery.
  • Real AI product delivery.
  • Strong engineering fundamentals.
  • Practical use of AI coding tools and agentic engineering workflows.
  • Ability to operate across cloud, local, and edge environments.
  • Security-conscious engineering judgment.
  • Clear documentation habits.
  • High personal accountability.
  • Understanding of clinical safety, patient data, audit, consent, and regulated healthcare environments.

We are less interested in candidates whose AI experience is limited to strategy presentations, superficial prompt usage, or experimental demos without implementation depth.

Senior Full Stack AI Engineer

Creative Thinking Institute / Regenemm Healthcare

Melbourne, Australia - On-site - Full-time

Release date: 4 May 2026

Current ask: Senior Full Stack AI Engineer for healthcare-grade AI product delivery.

Reporting to: Founder and CEO, Dr Brendan O'Brien - neurosurgeon, product owner, and software developer

Read before applying: Creative Thinking Institute and Regenemm Healthcare

CTA: Email bren@regenemm.com with subject line Application - Full Stack AI Engineer - Regenemm Healthcare.

About us

Regenemm Healthcare is building clinical AI infrastructure: secure, auditable, clinician-facing software that supports real care, not generic AI wrappers.

Our platform follows a Hub-and-Spoke architecture. The Hub governs clinical truth, consent, provenance, audit, orchestration, and interoperability. The Spokes deliver focused workflows across hospital care, home care, billing, patient communication, clinical documentation, medicolegal processes, and healthcare coordination.

We work alongside an internal ecosystem of approximately 30 AI agents that contribute to engineering, operations, architecture, documentation, research, and product workflows.

We are looking for a senior or exceptional mid-career engineer who can build production systems in this environment with judgment, care, and technical depth.

The ask

You will ship full-stack features across the Regenemm modules: Voice, Link, Hospital Hub, Home Hub, Billing, Edge Connector, and future clinical workflow systems, working from frontend through API, AI orchestration, data, and deployment.

You will integrate LLMs into real clinical workflows where accuracy, provenance, reviewability, auditability, patient-data protection, and failure-mode design matter.

This is a software engineering role, not a prompt-engineering-only role. You will work with our agentic coding setup as a force multiplier, not as a crutch.

Day to day, you will:

  • Design and build full-stack features in TypeScript/Next.js and Python/FastAPI.
  • Implement production AI features, including LLM integration, RAG, embeddings, vector search, tool/function calling, and evaluation harnesses.
  • Work with AI coding agents by reviewing, constraining, testing, and improving their output.
  • Deploy and operate services on AWS using Terraform, GitHub Actions, and modern observability.
  • Contribute to local and edge inference workflows where clinical, latency, resilience, or privacy requirements demand it.
  • Write code that meets healthcare-grade expectations for security, auditability, reliability, maintainability, and clinical review.
  • Document implementation decisions, assumptions, risks, failure modes, and trade-offs clearly.

Healthcare domain experience is non-negotiable

This role requires demonstrated healthcare domain experience.

Candidates must be able to show prior work in one or more of the following areas:

  • Healthcare, medtech, digital health, clinical software, hospital systems, or patient-facing health systems.
  • EMR/EHR workflows, FHIR, HL7, pathology/radiology/result feeds, or clinical interoperability.
  • Medical documentation, clinical workflow automation, patient communication, care coordination, or clinician-facing software.
  • Regulated health environments involving privacy, consent, audit, patient data, clinical safety, or operational governance.
  • Closely adjacent clinical technology where the candidate can clearly demonstrate healthcare implementation knowledge.

General AI experience without healthcare implementation experience is not sufficient for this role.

What we need to see

  • Demonstrable healthcare domain experience, as outlined above.
  • Production experience integrating AI into shipped healthcare, medtech, digital health, clinical software, or regulated patient-data systems.
  • Strong TypeScript and/or Python capability.
  • Comfort working across frontend, backend, APIs, data, and deployment.
  • Practical experience with LLMs, RAG, embeddings, evaluation systems, or AI agents.
  • AWS deployment experience and modern CI/CD practice.
  • Security-aware engineering habits.
  • Clear written documentation.
  • Ability to work in a founder-led, clinically informed product environment.
  • Ability to test, verify, and harden AI-enabled features rather than simply demonstrate promising behaviour.

Strongly preferred

  • Familiarity with FHIR, HL7, EMR/EHR systems, clinical documentation, or patient-data workflows.
  • Hands-on use of AI coding agents in real engineering workflows.
  • Experience with evaluation harnesses and regression testing for AI quality.
  • Familiarity with edge computing, local-device AI, hybrid cloud/local deployment, or local inference workflows.
  • Experience working closely with clinician founders, domain experts, or clinical product owners.
  • Familiarity with privacy, audit, consent, provenance, and secure data-handling requirements.
  • Experience with healthcare workflow design, clinician-facing interfaces, or patient communication systems.

Technical domains relevant to this role

You do not need to have used every tool or framework listed below. You do need real implementation ability across enough of this surface area to build production systems safely.

Frontend

  • TypeScript.
  • React / Next.js.
  • Tailwind or equivalent UI systems.
  • API-driven interfaces.
  • Secure authenticated workflows.
  • Accessibility-aware design.
  • Clinician-facing workflow design.

Backend

  • Python / FastAPI.
  • Node.js / Express.
  • REST APIs.
  • Structured data models.
  • Authentication and authorisation.
  • Database integration.
  • Event-driven or queue-based workflows.
  • Audit logging.
  • Secure file and document handling.

AI systems

  • LLM APIs and orchestration.
  • Retrieval-augmented generation.
  • Embeddings.
  • Vector databases.
  • Tool and function calling.
  • Agent frameworks or AI coding agents.
  • Evaluation harnesses.
  • Regression testing for AI quality.
  • Synthetic data workflows.
  • Local model testing and inference.
  • Prompt and context management.
  • Failure-mode analysis for AI outputs.

Infrastructure

  • AWS.
  • Docker.
  • Terraform or equivalent infrastructure-as-code.
  • GitHub Actions or equivalent CI/CD.
  • CloudWatch, logs, metrics, or equivalent observability tools.
  • Secrets management.
  • Secure networking.
  • Edge and local compute patterns.
  • Hybrid cloud/on-premise deployment.

Personal attributes

We are looking for an engineer who is:

  • Technically strong and implementation-focused.
  • Careful with clinical and sensitive data.
  • Able to work with AI tools without being over-reliant on them.
  • Clear in written documentation.
  • Willing to test and verify rather than assume.
  • Comfortable working in narrow, disciplined implementation lanes.
  • Able to distinguish prototype behaviour from production reliability.
  • Comfortable with clinical ambiguity and regulated-system constraints.
  • Able to work directly with clinician product owners and domain experts.

Compensation

  • Wage: To be discussed (TBD) + super.
  • Equity options in Creative Thinking Institute Pty Ltd.
  • Learning budget, conference support, and high-spec hardware.
  • Melbourne on-site.
  • Full work rights in Australia preferred; sponsorship may be considered for exceptional candidates.

How to apply

Email bren@regenemm.com with subject line:

Application - Full Stack AI Engineer - Regenemm Healthcare

Please include:

  1. CV or professional profile.
  2. GitHub, portfolio, product links, repositories, or links to shipped AI-integrated work.
  3. A brief description of your healthcare domain experience, including the clinical, operational, regulatory, interoperability, or patient-data context in which you worked.
  4. A short written response of no more than 400 words to: "Describe a production AI or healthcare software feature you built. What clinical or patient-data context did it operate in, what model and tools did you use, how was it integrated, how did you test it, and what failure modes did you need to control?"
  5. Two references who can speak directly to your implementation work.

Shortlisted candidates will be contacted directly.

Application materials will be reviewed by Dr Brendan O'Brien.

Our hiring standard

We are seeking candidates with strong implementation ability and verifiable healthcare software experience.

We are particularly interested in engineers who can demonstrate:

  • Real healthcare software delivery.
  • Real AI product delivery.
  • Strong engineering fundamentals.
  • Practical use of AI coding tools and agentic workflows.
  • Ability to operate across cloud, local, and edge environments.
  • Security-conscious engineering judgment.
  • Clear documentation habits.
  • High personal accountability.
  • Understanding of clinical safety, patient data, audit, consent, and regulated healthcare environments.

A candidate with strong general AI credentials but no healthcare implementation experience should not pass the first screen.

Creative Thinking Institute Pty Ltd is an equal opportunity employer. We welcome applicants of all backgrounds, and we particularly encourage applications from people underrepresented in healthcare technology.