AI Platform and Ops Lead – Assistant Vice President

• 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 and controlled 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

Requirements

• 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
• 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.

Core Competencies

Demonstrates expertise in designing, implementing, and managing secure enterprise AI platform environments across Azure, AWS, and private cloud. Proficient in automation, infrastructure-as-code, and operational strategies to ensure compliance, security, and resiliency in AI operations.

Highest-signal resume keywords

• Cloud Engineering
• Infrastructure-As-Code
• AI/ML Operations
• Terraform
• Kubernetes

ATS Optimization Keywords

Hard Skills

• Cloud Engineering
• Platform Engineering
• DevOps
• MLOps
• Terraform
• PowerShell
• Python
• Shell Scripting
• CI/CD Pipelines
• Disaster Recovery

Certifications & Qualifications

• Bachelor's Degree in Computer Science
• Bachelor's Degree in Math
• Bachelor's Degree in Engineering
• Bachelor's Degree in Information Technology

Industry Keywords

• Enterprise AI Solutions
• Regulated Financial Services
• Risk Management
• Operational Monitoring
• Business Continuity

Tools & Technologies

• Azure
• AWS
• Kubernetes
• Databricks
• Virtual Networks
• Secrets Management
• Object Storage
• File Stores
• AI/ML Studios
• LLM Services