
PRINCIPAL ENTERPRISE ARCHITECT - AI
- Virginia Beach, VA
- $106,080-176,821 per year
- Permanent
- Full-time
- Mapping the relationships between information systems components (i.e., end users, business processes, applications, data, IT platform hardware/software, and networks)
- Identifying key interactions and dependencies across separate systems and platforms
- Evaluating the total cost of ownership and return on investment of various architecture alternatives.
OR
10+ years of relevant experience in lieu of a degreeMaster’s degree in Computer Science, Information Systems, Engineering, or related field preferredCertification/LicensurePreferred AWS/Azure/Google Professional Architect, Certified Health Data Analyst (CHDA).Experience RequirementsRequired 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.