AI Platform and Ops Lead, Assistant Vice President
$90,000–$157,500 year
On-siteClifton, New Jersey, United States or Boston, Massachusetts, United States
Job Summary
Lead the design, implementation, and day-to-day operations of secure, well-managed enterprise AI platform environments across Azure, AWS, and private cloud. Configure and operationalize cloud services including Kubernetes, virtual machines, secrets management, and AI/ML studios while building automation scripts, infrastructure-as-code patterns, and deployment pipelines. Drive identity and access management, monitoring, alerting, and incident response strategies to ensure production readiness, resiliency, and compliance for regulated enterprise AI solutions. Partner with application, data, risk, cyber, and business teams to translate platform needs into reusable enterprise patterns and support disaster recovery planning.
Required Qualifications
- 4+ years of experience as a full-time IT professional in cloud engineering, cloud support, platform engineering, site reliability engineering, DevOps, MLOps, AI platform engineering, or cloud administration roles
- Experience designing, deploying, supporting, and operating Azure, AWS, or private cloud environments, including IaaS, PaaS, container platforms, managed services, and production support models
- 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
Desired Qualifications
- 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
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