Senior Cloud Engineer
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What you'll do
- 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.
What they're looking for
- 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 have
- 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
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
City/State
Norfolk, VAWork Shift
First (Days)Overview:
Overview
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.
Key Responsibilities
Cloud Platform Engineering
· 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.
AI and Data Platform Enablement
· 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.
DevSecOps, Reliability and Governance
· 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.
Education
- Bachelor's Degree (Preferred)
or
- Experience in lieu of Bachelor's degree - 7+ years of relevant experience without a Bachelor’s degree
Certification/Licensure
- Relevant Azure certifications preferred
Experience
Required Qualifications
· 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.
Preferred Qualifications
· 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 environmen

We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay range for full-time employment is $118,601.60 - $180,876.80 annually.

Additional compensation may be available for this role, such as shift differentials, standby/on-call pay, overtime, shift premiums, extra-shift incentives, or bonus opportunities. Compensation within the range may vary based on qualifications, experience, location, market conditions, and business needs. Note: If an annual salary is posted, it is based on a full-time colleague working 2,080 hours annually.
Benefits: Caring For Your Family and Your Career
• 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
•Colleagues have the opportunity to earn an annual discretionary bonus if established system and employee eligibility criteria is met.
Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves.
In support of our mission “to improve health every day,” this is a tobacco-free environment.
For positions that are available as remote work, Sentara Health employs associates in the following states:
Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.
Company
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