Senior AI Platform & Cloud Operations Lead

Jobtailor

Massachusetts

On-site

USD 140,000 - 180,000

Full time

14 days+

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Job summary

Jobtailor seeks an experienced Cloud Platform Engineer to lead enterprise AI environments across Azure, AWS, and private cloud. You will design, implement, and operate scalable, secure AI platforms with IaC, CI/CD, and automated runbooks.

The role requires deep experience with cloud services, Kubernetes, Databricks, security controls, and regulated environments. Collaboration with multiple teams is essential for reliable AI operations.

Qualifications

4+ years of experience as a full-time IT professional in cloud engineering, cloud support, platform engineering, SRE, DevOps, MLOps, or cloud administration roles.
Experience designing, deploying, and operating Azure, AWS, or private cloud environments including IaaS, PaaS, containers, managed services, and production support.
Experience with Terraform, Backstage, Harness, CI/CD pipelines, infrastructure-as-code, environment management, and deployment automation.
Experience with Virtual Networks, Kubernetes, VMs, Secrets Store, messaging, Object Storage and File Stores, databases, AI/ML studios, LLM Services, and Databricks.
Bachelor's degree in Computer Science, Math, Engineering, Information Technology, or a related technical field
Demonstrable experience deploying and supporting enterprise workloads in Azure, AWS, or private cloud with appropriate controls for security, resiliency, and operational monitoring
Proficiency with PowerShell, Python, shell scripting, or other automation languages used to manage cloud infrastructure and platform operations
Business continuity, disaster recovery, resiliency testing, incident management, or production support experience
Understanding of AI/ML lifecycle concepts, LLM services, model hosting patterns, responsible AI controls, MLOps, observability, and production readiness practices is preferred
Experience operating in a regulated financial services, risk-managed, or highly controlled technology environment is preferred.

Responsibilities

Lead the design, implementation, and day-to-day operations of secure, well-managed enterprise AI platform environments across Azure, AWS, and private cloud
Configure, manage, and operationalize cloud and platform services including Virtual Networks, Kubernetes, virtual machines, secrets management, messaging, object storage, file stores, databases, AI/ML studios, LLM services, and Databricks
Build and maintain automation scripts, infrastructure-as-code patterns, deployment pipelines, and repeatable platform runbooks to support scalable production releases
Use native Azure, AWS, and private cloud services to meet enterprise technology, security, resiliency, observability, and compliance requirements
Drive identity and access management, configuration management, monitoring, alerting, logging, incident response, and operational readiness strategies for AI platform workloads
Partner with application, data, risk, cyber, architecture, and business teams to translate platform needs into reliable AI operations capabilities and reusable enterprise patterns
Support production readiness reviews, resiliency testing, disaster recovery planning, vulnerability remediation, and platform control evidence required for regulated enterprise AI solutions
Contribute to platform standards, governance practices, documentation, service onboarding processes, and continuous improvement of AI platform operations