You will lead the end-to-end development of the AI solution, managing both internal and external technical development teams. The government is building a national AI-enabled health platform for Myopia to transform how citizens access, navigate, and receive relevant preventive and interventional healthcare services. This is a rare opportunity to architect and deliver a solution that operates at national scale, from the infrastructure underpinning clinical AI models to the citizen-facing interfaces through which patients book appointments, receive care guidance, and engage in their own eye care journeys. Your role involves collaborating with clinicians, data stewards, and compliance teams to align technology with clinical outcomes, driving vendor evaluations and proof-of-concepts, and establishing development standard operating procedures and solution specifications.
As Senior Principal Engineer, you will lead the end-to-end engineering of this platform. You will be responsible for both the technical architecture and the product engineering rigour that ensures the platform is safe, interoperable, and genuinely useful to the people it serves — patients, clinicians, and care coordinators alike. You will guide cross-functional teams across backend systems, data engineering, AI integration, and citizen-facing product development, ensuring that every layer of the solution is coherent, secure, and built to last. You will be required to architect scalable, secure, cloud-based solutions, ensuring high availability and data compliance with HIPAA, Personal Data Protection Act, and General Data Protection Regulation standards. Additionally, you'll integrate diverse clinical and operational systems through healthcare standards such as Fast Healthcare Interoperability Resources APIs. Your responsibilities include designing architectures aligned with Zero Trust Security and National Institute of Standards and Technology frameworks, overseeing implementation of identity and access management, encryption, and security monitoring, whilst conducting periodic security risk assessments.
Key Responsibilities:
Architecture & Solution Design:
- You will lead the design of a scalable, secure, cloud-based national health platform, architecting systems that span clinical AI inference, real-time data exchange, and patient-facing digital services.
- You will ensure that the platform is designed for high availability cloud-based solutions (across AWS, Azure, GCP and/or HCC), and compliance with HIPAA, the Personal Data Protection Act, and GDPR standards.
- You will ensure that its component architectures compose into a coherent whole rather than a collection of disconnected systems using best practices for software development lifecycle (SDLC) documentation (in compliance with IEC 62304) and management (in compliance with ISO13485).
- You will take ownership of the product engineering dimension of the platform — the direct-to-citizen interfaces and closed-loop workflows that make AI actionable for patients. This includes designing and overseeing the delivery of patient engagement surfaces (web, mobile, and conversational), health education and personalised information journeys, self-service appointment booking and scheduling integrations, and end-to-end referral coordination workflows that close the loop between AI-driven recommendations and real clinical action.
Cybersecurity & Compliance:
- Design architectures aligned with Zero Trust Security and NIST/CIS standards
- Oversee implementation of identity and access management (IAM), encryption, data masking, and security monitoring
- Collaborate with InfoSec teams to ensure compliance with healthcare data privacy and security frameworks
- Conduct periodic security risk assessments and architect remediation strategies
Software & Data Engineering:
- Guide teams in API-driven architectures using frameworks such as .NET, or Node.js
- Lead engineering of data pipelines for structured and unstructured healthcare data using Spark, Kafka, Airflow, Databricks, or Snowflake
- Establish data governance, metadata management, and ETL/ELT frameworks to support analytics and AI models
Data Science & GenAI Integration:
- Architect MLOps pipelines for AI model deployment, monitoring, and retraining
- Drive responsible AI practices ensuring model explainability, bias mitigation, and regulatory alignment
- Keep abreast of the emerging regulatory standards for AI in healthcare and work towards product alignment with them.
Health Promotion Platform & Content Engineering
- Lead the architecture and engineering of the platform's health promotion layer — the public-facing content surface through which citizens discover, engage with, and are guided toward the platform's clinical and transactional services.
- Ensure the content platform is engineered for discoverability, with server-side rendering and structured semantic markup that enables the platform to surface authoritative, government-endorsed (Health Promotion Board) and/or Physician-verified health information and/or Myopia-related solution listings in response to citizen health queries at the point of need.
- Design the content schema and metadata architecture in alignment with the platform's clinical taxonomy and care pathway logic, so that every piece of health promotion content carries structured intent signals — condition, care stage, recommended action — that drive contextual, automated calls-to-action into the platform's booking, triage, and referral functions.
- Integrate the content management system (CMS) with the platform's clinical governance framework, building first-class editorial workflows that include clinician review and sign-off, version history, scheduled content review cycles, and automated flagging when underlying clinical guidelines are updated.
- Ensure that this health promotion platform is not an island, whereby its data model, access controls, and audit trails must be coherent with the broader platform governance architecture.
Cloud, Networking, and Infrastructure:
- Design hybrid and multi-cloud architectures with Kubernetes, Docker, and Terraform
- Optimise performance and reliability using VPCs, load balancers, VPNs, and SDN technologies
- Oversee infrastructure as code (IaC), automated deployments (CI/CD), and cost optimisation strategies
- Integrate edge computing and IoT devices for hospital and clinical environments
Healthcare Standards & Interoperability:
- Deep understanding of FHIR (R4/5) and terminology standards such as ICD-10/11, DICOM
- Design and map healthcare data models to enable semantic interoperability across systems
- Deep understanding of clinical data standardisation, EHR integration, and FHIR-based data lakes
Job Requirements:
- Minimum Bachelor's degree in Computer Science, Biomedical Informatics, or related field with at least 10 years progressive experience in IT/Software architecture
- Proven expertise across software engineering, data architecture, cybersecurity, and healthcare interoperability.
- Strong working knowledge of healthcare data standards
- Cloud certifications (AWS Solutions Architect, Azure Architect Expert, or GCP Professional Architect).
- Experience with clinical informatics systems such as Epic, Cerner, or Meditech is advantageous
- Knowledge of healthcare regulatory standards including HIPAA, HITECH, PDPA, or ISO 27001 is beneficial
- Experience architecting or delivering content API platforms at scale, with an understanding of editorial governance workflows and the technical requirements of optimised, server-side rendered content delivery
- Strong technical leadership abilities with excellent communication skills to explain complex AI concepts to non-technical stakeholders
- Proactive and detail-oriented approach with ability to thrive in multi-stakeholder, fast-moving environments
- High integrity and commitment to safe, ethical AI design
Advantageous
- 5 years experience in healthcare technology will be beneficial, with experience working with clinical informatics systems such as Epic, Cerner, or Meditech
- Familiarity with healthcare regulatory standards including HIPAA, HITECH, PDPA, or ISO 27001
- Experience building platforms that integrate AI-generated recommendations into actionable patient or clinician workflows
- Ability to design content data models and taxonomies that serve both discoverability and downstream routing logic, connecting health promotion content directly to transactional platform functions
- Prior exposure to national-scale digital infrastructure programmes or large-scale interoperability initiatives
