Overview
On Site
Depends on Experience
Contract - W2
Skills
API
Agile
Amazon Web Services
Apache Kafka
Data Marts
Data Warehouse
DevSecOps
Artificial Intelligence
Enterprise Architecture
FEAF
Front Office
GRID
HIPAA
HL7
Health Care
Kubernetes
Machine Learning (ML)
Microsoft Power BI
Microsoft SQL Server
Machine Learning Operations (ML Ops)
Messaging
Microservices
Snow Flake Schema
Modeling
MongoDB
Orchestration
Privacy
PyTorch
RabbitMQ
Cloud Computing
Cosmos-Db
Tableau
TensorFlow
Zachman Framework
TOGAF
Docker
Solution Architecture
Job Details
Preferred AWS/Azure/Google Professional Architect, Certified Health Data Analyst (CHDA)
Required Qualification :
- 8+ years in enterprise architecture or solution architecture roles, with a minimum of 4 years focused on AI/ML initiatives in healthcare or similarly regulated industries.
- Prior experience leading enterprise-wide AI transformation in a large health system or national healthcare provider.
- Proficient with AI/ML frameworks (TensorFlow, PyTorch), MLOps toolchains (Kubeflow, MLflow), and container orchestration (Kubernetes, Docker).
- Deep understanding of API-first design, microservices architecture, messaging patterns (Kafka, RabbitMQ), and event streaming.
- Demonstrated track record integrating conversational AI/chatbot technologies across multiple back-office and front-office systems.
- Experience in technologies such as Cloud (Azure), Datawarehouse, Data mart, Data Lake, Data Fabric, Machine learning, mobile, and digital experience technologies.
- Experience with tools such as SQL Server, MongoDB, CosmosDB, Data Synapse, Data Bricks, Snowflake, Event Grid, Event Hub, Tableau, Power BI etc.
- Experience with Architecture frameworks such as TOGAF, DODAF, Zachman, FEAF etc. and specifically tailoring them to data-driven and AI-driven architecture domains.
- Skilled in agile and DevSecOps methodologies for rapid, secure delivery of AI solutions.
- Familiarity with healthcare interoperability standards (FHIR, HL7) and data privacy regulations (HIPAA, GDPR).
- Experience modeling architecture viewpoints in EA tools.
Preferred Qualifications (optional)
- Experience supporting enterprise-level AI/ML initiatives
- Knowledge of industry standards and frameworks (e.g., TOGAF, Zachman)
- Background in healthcare or large-scale enterprise environments
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.