Enterprise Data Governance, Vice President
state street bankAustin (TX)
Enterprise Data Governance, Vice President
Posted today
state street bankAustin (TX)
SENIORITY
Manager
About the role
Overview:
As VP, Agentic AI Engineering, you will own the strategy and architecture of State Street's enterprise agentic AI platform. You will set the vision for multi-agent orchestration, security, and governance across multi-cloud environments (AWS, Google Cloud, Azure). You will lead engineering talent, influence technology direction, and foster innovation in agentic AI to support enterprise-scale workloads. This role sits at the intersection of architecture, platform delivery, and executive governance, enabling secure, scalable AI systems that drive business impact. A strong hook is the opportunity to shape cloud-native agentic capabilities across the organization and partner with cross-functional Compensation / Benefits retirement plan with 401K company match comprehensive medical, dental, vision insurance paid time off including vacation and sick leave short-term disability and life insurance Employee Assistance Program incentive-based compensation
Responsibilities:
Own enterprise agentic platform strategy, architecture, roadmap, and governance with focus on multi-cloud scalability and resilience Drive innovation in multi-agent orchestration using frameworks and at-scale patterns Set and enforce standards for orchestration, A2A protocols, HITL, tenant IAM/RBAC, and runtime security across clouds Represent Agent Foundry and Runtime pods in governance forums and influence cloud adoption strategy Improve platform reliability, scalability, and cost optimization for agentic AI workloads across AWS, GCP, and Azure Build, lead, and develop engineering leadership across pods Partner with Architecture, Data/Knowledge, and Product teams for end-to-end platform strategy and delivery Foster continuous improvement and emerging best practices for cloud-native agentic platforms Oversee compliance, risk, and performance reviews for enterprise AI across public clouds
Key requirements:
12–17 years of relevant experience with leadership of large-scale, multi-agent or AI-driven platforms Bachelor’s or Master’s degree in Computer Science, Engineering, or related field Proficient in Python and familiarity with at least one other modern language (Java, Go, or C++) Strategic ownership of platform architecture and technology roadmaps for agentic AI systems Extensive hands-on and leadership experience with multi-cloud environments (AWS, Google Cloud, Azure) including security, governance, and cost optimization Proven track record in reliability, scalability, and incident management for AI systems Experience partnering with executive and cross-functional teams on platform strategy Experience building and developing engineering leadership and fostering innovation Expertise in compliance, risk management, and performance oversight for enterprise AI Excellent communication, governance, and stakeholder management skills strong communication stakeholder management leadership and people development Python Java Go
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.