AI Platform and Ops Lead, Assistant Vice President

About this role

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.

Why this role is important to us Our technology function, Global Technology Services (GTS), is vital to State Street and is the key enabler for our business to deliver data, insights, and trusted digital capabilities to our clients. We are driving the company’s digital transformation and expanding business capabilities using industry best practices and advanced technologies such as cloud, artificial intelligence, machine learning, automation, and robotics process automation. As AI adoption scales across the enterprise, secure and reliable platform operations are critical to helping teams move AI-enabled solutions from proof of concept into production. This role will help establish and operate the foundational capabilities required to deliver AI solutions that are resilient, compliant, observable, and aligned with enterprise architecture and risk expectations. We offer a collaborative environment where technology skills and innovation are valued in a global organization. We’re looking for technical talent to join our team and deliver practical technology solutions that help us become an end-to-end, next-generation financial services company. Join us if you want to grow your technical skills, solve real problems, and make your mark on our industry.

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, obser

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