Product Owner, AI Development Platform - Vice President

Morgan Stanley•New York, NY

About The Position

We’re seeking an experienced Product Owner to build out a firmwide AI Development Platform and drive the adoption of AI capabilities throughout the enterprise. Morgan Stanley has been at the forefront of the AI journey, building applications that use AI to provide better, personalized advice to our clients. Generative AI offers unique opportunities to provide new capabilities to both internal users and clients. The ideal candidate will have strong knowledge of AI and ML capabilities, including Generative AI. As a Product Owner, you will possess a strong understanding of the overall capabilities required to successfully deploy AI applications, such as AI models, cloud service provider capabilities, 3rd party vendor capabilities, and vector databases. The candidate will have a strong passion for helping users leverage AI to increase productivity and generate new ideas for product improvements. This role requires a strong understanding of the technical capabilities, available features, and the cost of deploying AI solutions. The successful candidate must demonstrate strong leadership, ownership, and accountability of the platform and products. In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. Since 1935, Morgan Stanley has been a global leader in financial services, continuously evolving and innovating to better serve our clients and communities in over 40 countries worldwide.

Requirements

Bachelor's or Master's degree in Computer Science or related field, or equivalent job experience.
10+ years of experience in software development/ software product management or related field.
10+ years of experience owning a product, balancing various stakeholder groups in a large enterprise environment.
Proven experience leveraging JIRA, Roadmunk, PowerPoint, Excel, or other productivity applications to effectively communicate product capabilities and delivery timelines.
Deep understanding of the AIML domain in general, latest developments and trends in Generative AI.
Understanding of AIML/GenAI capabilities on the major cloud providers, such as Azure, AWS, GCP.
Understanding of Responsible AI, AI Ethics and ability to articulate technical concepts effectively to diverse audiences.
Familiar with Information Security, concepts such as Defense in depth and zero trust.
Previous hands-on Application Development background in at least one prominent programming language, preferably Python.
Strong desire and ability to influence development teams and help them adopt AI.
Experience working in a large and regulated industry such as Financial Services, Insurance etc. and demonstrated ability to work effectively in a global organization and across time zones.

Responsibilities

Partner with business application teams to understand their requirements for Generative AI Platform Capabilities.
Manage a pipeline of new features, prioritize bug fixes, prioritize and address technical debt and other streams of work required to build and maintain the platform, and achieve consensus amongst multiple stakeholder groups on platform priorities.
Proactively manage stakeholders and customers' expectations on deliverables.
Build road maps for delivery of capabilities in conjunction with the engineering team for external and internal communication of platform vision, priorities, and committed deliverables.
Have a platform mindset and drive common, reusable solutions to scale Generative AI use cases.
Seek out consensus for major design decisions and product selection (build vs buy, 3rd party Vendor vs Open Source etc.) for building Generative AI platforms and solutions.
Author best practices on the Generative AI ecosystem, when to use which tools, available models such as GPT, Llama, Hugging Face etc. and libraries such as Langchain.
Understand and discuss the major challenges in this field related to Gen AI models, Data, Governance, Architecture etc.