Senior Cloud Engineer

Sentara Hospitals•Norfolk, VA

6d•Onsite

About The Position

Senior Cloud Engineer -AI Designs, implements, and operates secure, scalable cloud platforms that enable enterprise applications, AI, machine learning, analytics, and automation. This hands-on role is responsible for cloud infrastructure, Kubernetes, Infrastructure as Code, DevSecOps automation, and AI platform enablement across Azure and AWS, with a focus on security, reliability, observability, governance, and operational excellence.

Requirements

5+ years of experience in cloud, platform, infrastructure, or DevOps engineering.
Strong hands-on experience with Microsoft Azure and working knowledge of AWS.
Proficiency with Terraform, Bicep, Kubernetes, AKS, containers, GitHub, and CI/CD automation.
Experience supporting Azure Machine Learning, Azure AI Services, Azure OpenAI, or comparable AI platforms.
Experience deploying or supporting Databricks for data engineering, analytics, or machine learning workloads.
Strong understanding of cloud networking, identity, security, observability, resiliency, and operational support.
Strong analytical, troubleshooting, communication, and cross-functional collaboration skills.
Ability to work independently, navigate ambiguity, and provide technical guidance for complex initiatives.

Nice To Haves

Experience with Databricks Machine Learning, MLflow, Model Serving, Unity Catalog, and automated ML workflows.
Experience with LLMs, RAG, vector databases, agent frameworks, model evaluation, and AI observability.
Experience with MLOps, LLMOps, AgentOps, platform engineering, and developer self-service capabilities.
Experience in healthcare or another highly regulated environment.
Relevant Azure certifications preferred.
Bachelor's Degree or Experience in lieu of Bachelor's degree - 7+ years of relevant experience without a Bachelor’s degree

Responsibilities

Design, deploy, and support Azure and AWS infrastructure using Terraform and Bicep.
Build and operate Kubernetes environments, including Azure Kubernetes Service (AKS), container deployment, networking, scaling, and upgrades.
Develop reusable modules, platform services, automation, and guardrails that enable standardization and developer self-service.
Implement secure cloud networking, identity, access, connectivity, secrets management, monitoring, and resiliency patterns.
Build and support cloud platforms for AI, machine learning, generative AI, and advanced analytics workloads.
Design and operationalize environments for Azure Machine Learning, Azure AI Services, Azure OpenAI, and Databricks Machine Learning technologies, including MLflow and Model Serving.
Enable deployment of LLM, retrieval-augmented generation, vector database, and agent-based solutions through secure APIs and containerized services.
Implement model deployment pipelines, evaluation, observability, monitoring, and operational controls using MLOps, LLMOps, and AgentOps practices.
Design and maintain GitHub-based CI/CD pipelines with automated testing, security validation, deployment controls, and traceability.
Automate infrastructure provisioning, configuration, deployment, monitoring, and routine operations.
Troubleshoot complex cloud, Kubernetes, networking, security, performance, and deployment issues.
Ensure solutions align with enterprise architecture, cybersecurity, privacy, regulatory, and operational standards.
Partner with Enterprise Architecture, Cloud Architecture, Cybersecurity, Data Engineering, IT Operations, DevOps, and Application Development teams.

Benefits

Medical, Dental, Vision plans
Adoption, Fertility and Surrogacy Reimbursement up to $10,000
Paid Time Off and Sick Leave
Paid Parental & Family Caregiver Leave
Emergency Backup Care
Long-Term, Short-Term Disability, and Critical Illness plans
Life Insurance
401k/403B with Employer Match
Tuition Assistance – $5,250/year and discounted educational opportunities through Guild Education
Student Debt Pay Down – $10,000
Pet Insurance
Legal Resources Plan
Annual discretionary bonus