About the Role
The company's AI & Data team is looking for an experienced Healthcare AI & Data Solution Architect to lead the design and delivery of enterprise healthcare data and AI platforms across government and healthcare ecosystems. This is a senior, client-facing role for someone who can combine healthcare data architecture, interoperability, governance, AI delivery, and regulated solution design to translate strategic objectives into scalable, secure, and production-ready solutions.
Health Information Exchange (HIE) platforms are especially relevant for this role, as HIE enables secure sharing of patient information across different healthcare organisations, clinical systems, and ecosystem stakeholders.
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What You’ll Do
As a Healthcare AI & Data Solution Architect, you will shape enterprise data platforms, interoperability layers, analytics ecosystems, and AI-enabled solutions for large-scale healthcare transformation programmes. You will work closely with senior healthcare and government stakeholders, the company's delivery teams, cloud specialists, data engineers, cybersecurity experts, and responsible AI teams to design solutions that are secure, scalable, governed, and aligned to regulatory expectations.
- Lead end-to-end architecture for healthcare data and AI solutions, including lakehouse platforms, data integration layers, and analytics workbenches.
- Design enterprise healthcare data models, interoperability frameworks, and exchange patterns across hospitals, clinics, labs, insurers, and regulators.
- Architect HIE-enabled solutions that support secure data sharing across different EHR and clinical systems.
- Define AI-enabled solutions using ML, GenAI, and agentic AI for use cases such as predictive care, population health, capacity planning, and operational optimisation.
- Establish AI lifecycle, MLOps, and deployment approaches aligned to enterprise, clinical, and regulatory standards.
- Develop data governance controls covering data quality, metadata, cataloguing, consent, privacy, residency, security, and usage policies.
- Support operating model design, CoE setup, and broader data and AI capability building across the healthcare ecosystem.
- Act as a trusted advisor to senior stakeholders on data strategy, AI adoption, solution shaping, and transformation roadmap design.
What We’re Looking For
We are looking for a senior architect who can operate beyond strategy and prototypes, with the ability to design healthcare data and AI solutions for real enterprise and regulated environments. The ideal candidate will bring:
- 10–15 years of experience in data, AI, cloud, solution architecture, healthcare technology, or large-scale digital transformation.
- Strong exposure to healthcare or public-sector transformation programmes.
- Experience designing enterprise-scale data platforms, interoperability layers, integration patterns, and analytics ecosystems.
- Track record across end-to-end transformation, from strategy and architecture through to implementation and production delivery.
- Ability to communicate complex technical topics clearly to senior healthcare, government, business, and technology stakeholders.
- Consulting experience or significant client-facing delivery experience in complex multi-stakeholder environments.
Technical Expertise
- Data architecture: lakehouse, distributed data platforms, data mesh, data integration layers, and analytics workbenches.
- Interoperability: HIE, HL7, FHIR, integration engines, API layers, exchange patterns, and cross-organisation data sharing.
- AI stack: ML, GenAI, agentic AI, MLOps, AI lifecycle management, and AI platform integration.
- LLM / GenAI platforms: hands-on experience with enterprise LLM platforms such as Azure OpenAI, OpenAI GPT, AWS Bedrock, or Google Vertex AI, applied to healthcare use cases.
- Healthcare NLP and document intelligence: exposure to clinical summarisation, coding support, discharge note extraction, medical document search, and care pathway assistance.
- Safe AI in healthcare: understanding of prompt governance, grounding/RAG, human-in-the-loop review, clinical validation, and responsible AI controls.
- Data management: governance, cataloguing, metadata, quality, access controls, consent, privacy, and data residency.
- Cloud platforms: Azure, AWS, or GCP, with an understanding of secure and scalable enterprise architecture patterns.
Healthcare Domain Experience
- Experience working with clinical, claims, insurance, pharmacy, and regulatory reporting data.
- Experience with HIE or equivalent cross-organisation health exchange environments.
- Exposure to health analytics use cases such as population health, patient risk stratification, care coordination, capacity planning, and operational performance.
- Comfortable operating in regulated environments with senior healthcare, government, and ecosystem stakeholders.
Nice to Have
Experience in any of the following would be a strong advantage:
- Previous work on national, emirate-level, or large healthcare data platforms.
- Experience bridging healthcare strategy, data governance, interoperability, and AI delivery.
- Familiarity with healthcare privacy, consent management, data residency, clinical validation, and responsible AI requirements.
- Experience with cloud-native healthcare data platforms, modern integration stacks, and secure API-based architectures.
- Arabic language skills or previous work in the GCC healthcare ecosystem.
Technologies You May Work With
Azure OpenAI, OpenAI GPT, AWS Bedrock, Google Vertex AI, Azure AI Foundry, Databricks, Snowflake, lakehouse platforms, data mesh, FHIR, HL7, HIE platforms, integration engines, API management, RAG, vector databases, healthcare NLP, document intelligence, MLOps, MLflow, Kubernetes, Terraform, data catalogues, metadata management, and enterprise governance platforms.
Why Join the company AI & Data in the UAE?
You will work on high-impact healthcare, public-sector, and AI transformation programmes with leading organisations across the UAE and the wider region. This is an opportunity to help shape how healthcare ecosystems adopt data, AI, interoperability, and responsible AI securely and at scale, while contributing to one of the region’s fastest-growing transformation agendas. The role sits at the intersection of enterprise healthcare architecture, cross-ecosystem data exchange, emerging AI capabilities, and trusted, production-ready solution delivery.
