Transform healthcare for those Ascension serves and those who serve by delivering brand-wide digital experiences powered by people, design, data, AI, and technology
Requirements
- Expertise in architecting and delivering scalable, highly available, consumer-facing digital platforms
- Strong experience with AI systems, including model integration, inference services, vector databases, embeddings, and retrieval-augmented generation (RAG)
- Hands-on knowledge of AI and data platforms (e.g., GCP Vertex AI, Azure AI, OpenAI ecosystem, open-source ML frameworks)
- Experience with modern search, integration, microservices, and data technologies (GraphQL/REST, Spring Boot, Cloud SQL, NoSQL)
- Experience with observability platforms (e.g., Dynatrace, Datadog) and AI/model monitoring
- Cloud-native experience in GCP and/or Azure, including healthcare-specific services
- Strong understanding of healthcare interoperability standards (FHIR, HL7) and regulations (HIPAA, Cures Act), especially as applied to AI
Responsibilities
- Lead engineering teams for multiple strategic digital products, accountable for planning, delivery, quality, reliability, and operations
- Own technical design decisions, including functional and non-functional requirements such as scalability, security, performance, and resiliency
- Define and execute the AI engineering strategy for digital products, aligned with Ascension’s enterprise AI, data, privacy, and security strategies
- Lead the design, development, and productionization of AI-enabled solutions, leveraging generative AI, intelligent search, personalization, and recommendations
- Establish best practices for LLMOps, including model lifecycle management, prompt engineering, evaluation, monitoring, and retraining
- Embed DevSecOps, Infrastructure as Code, CI/CD, and automated quality gates across software and AI pipelines
- Drive a strong SRE and production ownership mindset, including incident response, reliability engineering, and cost optimization
Other
- High School diploma equivalency with 5 years of applicable cumulative job specific experience required, with 2 of those years being in leadership/management
- Excellent written and verbal communication skills
- Curious about technology and AI: Actively explores how emerging technologies and AI can improve patient, clinician, and associate experiences
- Continuous learner: Invests in ongoing growth for self and teams, especially in rapidly evolving AI and engineering domains
- Change-ready leader: Navigates ambiguity, drives transformation, and leads teams through technological and organizational change
