Data – AI Agents, Vice President

State Street•Boston, MA

About The Position

The Vice President, Data – AI Agents leads day-to-day delivery of the Data workstream supporting enterprise AI and agentic AI capabilities. The role ensures AI-agent use cases have access to authoritative, high-quality, appropriately governed, permissioned, and traceable data, and that data requirements are understood and addressed before solutions move into production. Working with Business, Data, AI Engineering, Architecture, Information Security, Identity and Access Management, Risk, and Governance teams, the VP translates AI use-case requirements into practical data solutions and drives their implementation. The position has practical delivery responsibility across data discovery, readiness, access and entitlements, quality, grounding and provenance, and production controls. It produces and maintains readiness assessments, source inventories and mappings, ownership documentation, classification and entitlement requirements, quality assessments and remediation plans, lineage and provenance documentation, integration requirements, data-related risks and dependencies, and production monitoring requirements. Success is measured by timely readiness assessments; identification of authoritative sources and accountable owners; resolution or escalation of material quality and access issues; appropriate entitlements and traceability; reuse of enterprise capabilities; effective management of production data issues; and clear reporting of risks, dependencies, and readiness.

Requirements

Strong experience in data management, data architecture, data governance, data analysis, or data transformation.
Practical experience delivering complex data initiatives within a large enterprise.
Strong understanding of data quality, metadata, lineage, classification, and data lifecycle concepts.
Working understanding of Generative AI and large language model concepts, particularly RAG, grounding, and enterprise search.
Understanding of structured and unstructured enterprise information.
Knowledge of data-access controls, entitlements, and identity/access-management principles.
Experience working with business and technology stakeholders to define requirements and deliver data solutions.
Strong problem-solving skills, including identifying data dependencies and driving issues to resolution.
Strong written and verbal communication skills, including explaining complex data issues to non-technical stakeholders.
Demonstrated delivery leadership, technical credibility, stakeholder management, risk awareness, constructive challenge, and execution discipline.

Nice To Haves

Experience in a regulated or highly controlled environment.
Experience supporting AI, machine learning, or advanced analytics solutions.
Familiarity with cloud and enterprise data platforms.
Exposure to Microsoft Azure AI Foundry, Microsoft Purview, Collibra, Databricks, or Snowflake.
Understanding of APIs, data lakes/lakehouses, semantic or vector search, and enterprise knowledge-management solutions.
Experience working with Role-Based Access Control (RBAC) or Attribute-Based Access Control (ABAC).
Experience supporting data governance, data readiness, or technology-risk assessments.

Responsibilities

Lead Data workstream delivery for assigned AI-agent use cases from initial assessment through production.
Translate business and AI-agent requirements into data requirements, dependencies, and delivery plans.
Identify required structured and unstructured data sources and establish the appropriate authoritative source.
Coordinate with Data Owners and Data Stewards to confirm ownership, permitted usage, and data readiness.
Perform and coordinate AI Data Readiness assessments, identify gaps, and drive remediation.
Assess data quality, freshness, completeness, and suitability for AI-agent use.
Support data patterns for APIs, retrieval-augmented generation (RAG), grounding, enterprise search, and semantic retrieval.
Ensure metadata, classification, lineage, and provenance are established for information consumed by AI agents.
Work with Security and IAM teams to implement appropriate user, agent, and service-identity entitlements.
Ensure AI retrieval and grounding solutions respect underlying data-access restrictions and do not create unintended access paths.
Support requirements for agent memory, contextual information, AI-generated data, retention, and traceability.
Define and coordinate data validation and testing before production deployment.
Establish operational monitoring for data availability, freshness, quality, access, and retrieval.
Track data issues, dependencies, and risks, and escalate material blockers to the VP Data Stream Lead and relevant governance forums.
Identify opportunities to reuse existing enterprise data capabilities rather than creating bespoke integrations for individual agents.
Maintain documentation and evidence demonstrating that Data requirements and controls have been addressed.
Produce and maintain AI Data Readiness assessments, data source inventories, source-to-use-case mappings, ownership and stewardship documentation, classification and entitlement requirements, quality assessments and remediation plans, lineage and provenance documentation, RAG/grounding and integration requirements, risk and dependency records, monitoring requirements, and readiness status for governance and implementation forums.

Benefits

Retirement savings plan (401K) with company match.
Basic life, medical, dental, vision, long-term disability, and other optional insurance coverage.
Paid time off, including vacation, sick leave, short-term disability, and family care responsibilities.
Access to an Employee Assistance Program.
Eligibility for annual performance-based incentive awards, with certain sales-role exceptions.
Eligibility for certain tax-advantaged savings plans.
Inclusive development opportunities.
Flexible work-life support.
Paid volunteer days.
Employee networks.