Vice President - Product Owner, AI Development Platform

Morgan Stanley•New York, NY

54d•$150,000 - $210,000

About The Position

We're seeking someone to join our team as an experienced Product Owner that will be responsible for building out a firmwide AI Development Platform and driving 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 provides further unique opportunities to provide new capabilities to the firm's internal users as well as our clients. The ideal candidate will have strong knowledge of AI and ML capabilities including Generative AI. As a Product Owner, you will come in with 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, vector databases etc. The candidate will have a strong passion for helping our users use AI to increase productivity as well as help 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 be able to 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 is known as a global leader in financial services, continuously evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.

Requirements

Bachelor's or Master's degree in Computer Science or related field, or equivalent job
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 to 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 talk about the major challenges in this field related to Gen AI models, Data, Governance, Architecture etc.

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