AI Platform and Ops Lead – Assistant Vice President

State Street

. Lead the design, implementation, and day-to-day operations of secure enterprise AI platform environments across Azure, AWS, and private cloud .

Posted 10/9/2026full-timeUnited StatesSenior💰 $90,000 - $157,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and managing secure enterprise AI platform environments across Azure, AWS, and private cloud, with a strong focus on automation, operational readiness, and compliance. Proficient in leveraging cloud services, infrastructure-as-code, and incident management to ensure resilient and efficient platform operations.

Highest-signal resume keywords

Cloud EngineeringInfrastructure-As-CodeTerraformKubernetesAI/ML Lifecycle Concepts

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Cloud EngineeringPlatform EngineeringInfrastructure-As-CodeAutomation ScriptingVirtual NetworksKubernetesDatabasesAI/ML StudiosCI/CD PipelinesDisaster Recovery

Soft Skills

Critical ThinkingProblem SolvingDecision-MakingOwnership MindsetEffective Communication

Tools & Technologies

AzureAWSTerraformPowerShellPythonDatabricksBackstageHarnessSecrets ManagementMessaging

Industry Keywords

Enterprise AIOperational ReadinessComplianceResiliency TestingIncident ManagementRegulated Financial ServicesRisk ManagementCloud AdministrationMLOpsProduction Support

Tech Stack

Tools & technologies

AWSAzureCloudKubernetesPythonShell ScriptingTerraform

About the role

Key responsibilities & impact

Lead the design, implementation, and day-to-day operations of secure 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
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
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 for regulated enterprise AI solutions
Contribute to platform standards, governance practices, documentation, service onboarding processes, and continuous improvement of AI platform operations

Requirements

What you’ll need

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
Strong critical thinking, problem solving, and decision-making skills
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, including 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

Benefits

Comp & perks

Retirement savings plan (401K) with company match
Basic life insurance
Medical insurance
Dental insurance
Vision insurance
Long-term disability insurance
Optional additional insurance coverages
Paid vacation leave
Paid sick leave
Short-term disability
Family care leave
Employee Assistance Program
Incentive compensation, including eligibility for annual performance-based awards
Certain tax-advantaged savings plans
Inclusive development opportunities
Flexible work-life support
Paid volunteer days
Employee networks