Job Description

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.