AICS (an ASUS company) seeks a visionary leader to pioneer the next generation of healthcare data architecture—empowering clinical, operational, and research excellence in the age of AI. Our mission: unify and harness vast, diverse healthcare data (hospital, claims, wearables, biobank, lifestyle, imaging) and deliver it at scale for actionable AI-driven intelligence and business insights.

What You’ll Do

• Architect and lead end-to-end healthcare data platforms, integrating data lake, warehouse, and mart solutions that serve a full spectrum of AI, BI, real-time, and analytics applications—designed for compliance, scale, and flexibility. 
• Drive adoption of agentic and multi-agent AI architectures, where autonomous and collaborative AI agents ingest, analyze, and orchestrate data and decision flows across the data ecosystem—enabling everything from workflow automation to personalized patient care. 
• Build platforms that enable collaboration between AI agents, clinicians, and applications, using advanced protocols and secure data sharing to facilitate seamless, real-time, human-in-the-loop intelligence and operational decision support. 
• Ensure pipelines enable agents to ingest and harmonize structured and unstructured data from EHR, biobank, lifestyle, and population sources—powering analytics, large language models, and advanced machine learning. 
• Champion a modern engineering culture: platform thinking, automation, CI/CD, prompt engineering, responsible and explainable AI, and continuous learning from the AI frontier.

About You

• Degree in Computer Science, Engineering, or related field.
• At least 8 years in data, platform, or AI engineering roles; 3+ years leading or managing technical teams.
• Hands-on experience architecting cloud-scale data lakes, warehouses, and marts, especially for healthcare, with deep familiarity in healthcare data integration, compliance, and privacy. 
• Experience designing and deploying multi-agent AI systems (orchestrating specialized AI agents, generative AI, prompt engineering, retrieval-augmented generation, context-aware data orchestration) in production. 
• Familiarity with interoperability standards (FHIR, OMOP), event-driven and API-based platforms, and secure, regulated healthcare data environments.
• Passion for empowering humans with AI—championing innovation, explainability, and collaboration in the design and delivery of next-gen healthcare intelligence solutions.