AI Engineering VP

Your Team Responsibilities

MSCI’s AI Engineering division is building a next-generation platform to enable the sustainable deployment and validation of intelligent systems across internal and client-facing services. As a Vice President in MSCI’s Core AI teams you will be directly responsible for ensuring execution across MSCI’s shared AI platforms, connecting AI agents with services, data, and operational logic across the firm. This role will shape governance, design standards, and tooling used to define and manage these interfaces for MSCI's internal users and future external partners.

Your Key Responsibilities

Responsibilities:

• Contribute to the evolution of AI integrations and discoverability tooling across internal and external-facing platforms.

• Establish integration standards and governance mechanisms for AI/data connectivity with internal APIs and services.

• Drive value creation on top of MSCI Services inside industry AI Solutions like ChatGPT, Claude, AgentSpace and others.

• Drive cross-cloud implementation (Azure, GCP) of low-latency, secure, and entitlement-aware integration methods for agent workflows.

• Partner with AI/ML platform teams to define APIs and patterns enabling real-time model supervision, feedback, and optimization.

• Work with legal, compliance, and risk partners to meet data security, privacy, and sovereign hosting requirements across geographies.
• You will collaborate closely with engineers, AI researchers, product leads, and control functions to establish reliable patterns and services that drive efficiency, improve validation and observability, and uphold MSCI’s standards for privacy, entitlements, and governance.

Your skills and experience that will help you excel

Desired Experience and Qualifications:

• Proven leadership experience in technical product/platform teams, ideally within ML infrastructure or enterprise integration domains.

• 10+ years of relevant experience in AI engineering roles, managing client facing solutions at scale

• Strong knowledge of API design, identity & access management, entitlement models, and service mesh/network security in GCP and/or Azure environments.

• Familiarity with LLMs, agents, orchestration frameworks, and the data/validation challenges they pose.

• Track record of designing developer tooling and protocols used by distributed teams.

• Ability to align complex technical needs with regulatory and operational requirements in large financial organizations.