We are in search of an AI Platform and Ops Lead, Assistant Vice President with a strong background in Generative AI, Machine Learning, enterprise architecture, cloud platforms, platform operations, and scalable solution delivery. The ideal candidate will have hands-on experience designing, deploying, operating, and continuously improving secure, resilient, compliant AI platforms across Azure, AWS, and private cloud environments. This role requires depth in cloud infrastructure, AI/ML platform services, automation, production monitoring, identity and access management, operational resiliency, and governance controls. The candidate should be able to partner across business, engineering, security, data, architecture, and risk teams to enable reliable, responsible, and production-ready AI solutions for enterprise use cases. 

What you will be responsible for 

As AI Platform and Ops Lead, Assistant Vice President in the CDAIO Organization, you will 

• 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. 

What we value 

These skills will help you succeed in this role 

• Strong critical thinking, problem solving, and decision-making skills with the ability to operate in a complex enterprise technology environment. 

• Demonstrated ownership mindset, operational discipline, and ability to drive issues from identification through resolution. 

• Experience working with large, global, and diverse teams across multiple locations and functions. 

• Good understanding of cloud services in AWS, Azure, or private cloud, with practical knowledge of enterprise security, networking, and resiliency expectations. 

• Ability to communicate effectively with technical and non-technical stakeholders and convert operational needs into clear actions, standards, and deliverables. 

• Interest in responsible AI, platform governance, automation, observability, and continuously improving operational maturity. 

Education & Preferred 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. 

• 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.