AI engineer C2C jobs
AI Engineer – Azure Cloud Infrastructure
Richmond, VA, hybrid local with Dl copy
Contract
Local proof needed
Job Summary
We are seeking an experienced AI Engineer IV to design, implement, optimize, and maintain Azure cloud infrastructure that supports enterprise-level AI/ML workloads. The ideal candidate will have deep hands-on expertise in Azure services, Infrastructure as Code (IaC), CI/CD automation, observability/monitoring, and scalable AI solution delivery. This role requires on-site presence in Richmond, VA on designated days.
Key Responsibilities
Azure Cloud Infrastructure (Core)
Design, implement, and maintain Azure cloud environments supporting AI/ML platforms.
Manage and optimize Azure compute, storage, networking, and security configurations.
Implement Azure services such as AKS, Azure ML, ADF, Azure Functions, Service Bus, Key Vault, APIM, VNets, and Load Balancers.
AI/ML Platform Support
Deploy, manage, and support AI/ML workloads (training, inference, pipelines) on Azure.
Ensure scalability, reliability, and performance of AI infrastructure.
Work closely with Data Scientists and ML Engineers on model deployment, versioning, and operationalization.
Infrastructure as Code (IaC)
Develop and maintain IaC using Terraform / Bicep / ARM Templates.
Ensure environment consistency, repeatability, and compliance with enterprise security standards.
Automate provisioning and configuration of AI infrastructure.
CI/CD Pipelines
Build and maintain CI/CD pipelines using Azure DevOps / GitHub Actions.
Automate build, test, deployment, and monitoring workflows for AI workloads.
Enable DevSecOps practices, including policy checks, vulnerability scanning, and workflow automation.
Monitoring & Observability
Implement and manage observability tools such as Azure Monitor, Log Analytics, Application Insights, and Grafana.
Configure alerts, dashboards, metrics, and logging for proactive system monitoring and resource optimization.
Troubleshoot performance issues and conduct root cause analysis (RCA).
Security, Compliance & Governance
Implement cloud security best practices, RBAC, policies, and identity governance.
Work with cybersecurity teams to meet enterprise compliance requirements (e.g., NIST, SOC2).
Ensure secure deployment, encryption, and access control for AI environments.
Collaboration & Documentation
Work with cross-functional teams including Data Science, Cloud Engineering, Architecture, and Security.
Create detailed documentation for architecture, operations, deployments, and environment configurations.
Provide mentorship to junior engineers and contribute to technical design discussions.
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent experience.
8–12+ years of experience in cloud engineering or DevOps.
5+ years hands-on experience with Azure cloud services.
Strong experience with Terraform / Bicep / ARM for IaC.
Proven expertise with Azure DevOps / GitHub Actions CI/CD pipelines.
Experience supporting AI/ML pipelines, Azure ML, AKS, Databricks, or similar technologies.
Strong knowledge of monitoring tools, cloud networking, and enterprise security practices.
Proficiency in scripting with Python, PowerShell, or Bash.
Preferred Qualifications
Azure Certifications (AZ-305, AZ-400, DP-203, AI-102, or similar).
Experience with Kubernetes (AKS), Docker, and containerized AI deployments.
Experience with MLOps frameworks and model lifecycle management.
Previous experience in a large enterprise or regulated industry.
To apply for this job email your details to sam.ss@anviktek.com