Principal Cloud Engineer – AI/ML

Elevance Health•Atlanta, TX

10h•Hybrid

About The Position

At Elevance Health, we are transforming how AI and machine learning drive healthcare innovation and outcomes just as much as we are driving how cloud at Elevance Health leverages these cutting-edge tools to enhance our offerings to our business. The Principal Cloud Engineer – AI/ML serves as a strategic technical leader responsible for defining and governing enterprise Cloud AI/ML platforms and capabilities. This role focuses on authoring and leading strategies and implementations for scalable ML systems, MLOps, and responsible AI which are aligned with healthcare regulatory requirements. This person will work with business and technology stakeholders to build a holistic view of the organizations strategy, processes, information and technical assets to ensure business and IT alignment.

Requirements

Requires an BA/BS degree in Information Technology, Computer Science or related field of study and a minimum of 8 years experience in architecture/design in relevant technology disciplines; or any combination of education and experience, which would provide an equivalent background.

Nice To Haves

Familiarity with feature stores, model registries, experiment tracking
Experience with streaming/inference pipelines
Strong background in responsible AI and model governance
Strong expertise in data security
Experience with infrastructure-as-code and automation tools such as Terraform or CloudFormation
Hands on experience with AI tooling; IDE and Services
Experience working with a variety of executives and their teams in a matrixed environment to deliver value and drive change.
Cross-functional experience (e.g., strategy, change management, business process management)
Experience with healthcare AI use cases
Understanding of networking concepts including VPCs, subnets, firewalls, and zero trust models
Experience implementing DevSecOps and secure CI/CD pipelines
Experience working in regulated environments, preferably healthcare

Responsibilities

Define enterprise AI/ML architecture strategy across multiple cloud providers (AWS, Azure, GCP)
Author and evangelize whitepapers/position papers defining principals and strategies for AI/ML cloud platforms.
Liaison with Enterprise Architecture, Enterprise Data and Analytics, and Information Security teams to design and enhance end-to-end ML pipelines including data ingestion, feature engineering, training, deployment, and monitoring.
Establish ML Ops standards for cloud (CI/CD for ML, model registry, feature store, monitoring) and cloud control frameworks to support these.
Drive adoption of responsible AI, model governance, and risk management frameworks
Partner with data science teams to operationalize models at scale.
Serve as a technical ‘Sherpa’ for Elevance projects leveraging AI/ML in any public cloud provider.
Evaluate and implement ML platforms (SageMaker, Vertex AI, Azure ML, Databricks ML, etc).
Enable real-time and batch inference architectures.
Establishes overall systems architecture vision and ensures specific components are appropriately designed and leveraged; contributes to the holistic vision of Enterprise Architecture.
Maintains components of architecture strategy and vision.
Maintains enterprise level blueprints.
Coordinates all enterprise-level conceptual architecture components (e.g., data architecture, application architecture, technical architecture.
Monitors usage of architectural components and assumes responsibility for reuse.
Drives system migration based upon roadmaps defined in enterprise and domain blueprints.
Leads architecture strategy and vision for enterprise.
Ensures blueprints are refreshed as needs emerge or in accordance to plan of record changes.
Provides continuous consulting services and direction in projects and architectures.
Champions and responsible for enterprise level technology and architectural standards, guidelines, principles, frameworks, and reference models.