AI Platform and Ops Lead, Assistant Vice President

State Street

Confirmed live today High trust
Closes in 3 days

Quick summary

Work type
On-site
Location
Boston, MAPrinceton, NJClifton, NJAustin, TXQuincy, MA
Salary
$90,000–$157,500 / yr
Employment
Full-time
Posted
18 days ago
Freshness
Confirmed live today
Closes
Oct 30, 2026 (soon)

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $194k
This role $124k
$73k $247k
below market most similar roles pay here above market

This role pays less than 91% of similar roles. Most pay $157,200–$230,100 — the blue band above. At the midpoint, this role pays about $124k versus about $194k for comparable roles.

Based on 240 similar postings.

Employer

About State Street

State Street Corporation is one of the world''s largest custodian banks and asset managers, providing investment servicing, investment management, and investment research to institutional investors. Industry: Financial Services & Asset Custody

State Street currently has 351 open roles on FindRole.

Listed pay typically runs $115,000–$195,944 across 199 roles with salary data.

Most-posted roles

View all roles at State Street

At a glance

TL;DR · AI Platform and Ops Lead, Assistant Vice President

The AI Platform and Ops Lead, Assistant Vice President joins the CDAIO Organization to lead the design, implementation, and day-to-day operations of secure enterprise AI platform environments. This role involves managing cloud services across Azure, AWS, and private cloud environments, specifically configuring Kubernetes, virtual machines, databases, and Databricks. You will build automation scripts, infrastructure-as-code patterns, and deployment pipelines to support scalable production releases. Key responsibilities include driving identity and access management, monitoring, and incident response while ensuring compliance for regulated enterprise AI solutions. You will utilize tools like Terraform, Backstage, and Harness alongside Python and PowerShell. The position solves the technical challenge of moving AI-enabled solutions from proof of concept into production by establishing resilient, observable, and governed platform capabilities within a complex enterprise technology environment.

What you'll do

  • Lead the design, implementation, and day-to-day operations of secure enterprise AI platforms across Azure, AWS, and private clouds.
  • Configure and manage cloud services including Kubernetes, virtual machines, secrets management, databases, and Databricks.
  • Build and maintain automation scripts, infrastructure-as-code patterns, and deployment pipelines for scalable production releases.
  • Drive identity and access management, monitoring, alerting, logging, and incident response strategies for AI workloads.
  • Support production readiness reviews, resiliency testing, disaster recovery planning, and vulnerability remediation for regulated AI solutions.
  • Translate platform needs into reliable AI operations capabilities and reusable enterprise patterns with data, risk, and security teams.
  • Contribute to platform standards, governance practices, documentation, and continuous improvement of AI platform operations.

What we're looking for

  • 4+ years of experience as a full-time IT professional in cloud engineering, platform engineering, SRE, DevOps, MLOps, or AI platform engineering.
  • Bachelor's degree in Computer Science, Math, Engineering, Information Technology, or a related technical field.
  • Experience designing, deploying, and operating Azure, AWS, or private cloud environments including IaaS, PaaS, and container platforms.
  • Proficiency with PowerShell, Python, shell scripting, or other automation languages to manage cloud infrastructure and platform operations.
  • Experience with Terraform, Backstage, Harness, CI/CD pipelines, infrastructure-as-code, and deployment automation.
  • Experience with Virtual Networks, Kubernetes, VMs, Secrets Store, messaging, Object Storage, databases, AI/ML studios, LLM Services, and Databricks.
  • Experience with Business Continuity, Disaster Recovery, resiliency testing, incident management, or production support.
  • Understanding of AI/ML lifecycle, LLM services, MLOps, and responsible AI controls is preferred.
  • Experience operating in a regulated financial services or highly controlled technology environment is preferred.

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