Enterprise AI - Technical Product Owner - Vice President

Enterprise AI at Morgan Stanley is seeking a Technical Product Owner (Vice President) to lead firmwide infrastructure platform products that enable application developers to build agentic AI applications. The role will own the vision, strategy, roadmap, adoption, and ongoing evolution of either the Agentic Development Framework or the Agentic Control Plane, requiring strong technical judgment and the ability to align diverse stakeholders.

Role Summary

You will establish product direction for a developer-facing platform area, synthesizing developer needs and technical feasibility to produce executable roadmaps. Responsibilities include driving consensus across engineering, architecture, and platform partners, translating complex enterprise requirements into prioritized product decisions, and defining measurable product outcomes spanning adoption, reliability, operational performance, and risk reduction.

Key Responsibilities

• Own the product vision, strategy, and roadmap for either the Agentic Development Framework or Agentic Control Plane.
• Form product direction by synthesizing application developer requirements with input from engineering leads, architects, control partners, platform teams, and other technology stakeholders.
• Drive technical and product consensus across stakeholders with differing perspectives, converting complex technical choices and enterprise constraints into clear priorities and decisions.
• Represent the needs of developers building agentic AI applications, identify friction across the development lifecycle, and shape APIs, frameworks, tooling, integration patterns, documentation, and onboarding experiences that support effective application build and operation.
• Translate the product vision into a prioritized roadmap and backlog, balancing strategic platform capabilities, developer demand, technical enablers, defects, technical debt, operational needs, and dependencies.
• Partner closely with engineering and architecture to assess technical feasibility and make informed product decisions across architecture, APIs and interfaces, interoperability, security, scalability, reliability, performance, developer experience, operational complexity, and cost.
• Shape major design decisions, including build-versus-buy and open-source-versus-vendor, in partnership with engineering and architecture.
• Drive common, reusable infrastructure capabilities and patterns to avoid point solutions and enable application teams to adopt and scale agentic AI effectively.
• Communicate product vision, value proposition, roadmap, priorities, technical decisions, and progress clearly to application developers, engineering and architecture teams, senior technology leaders, control partners, and external technology partners.
• Define and monitor meaningful product outcomes, including developer adoption, developer experience, platform effectiveness, reliability, operational performance, and risk reduction.
• Monitor developments in the AI, agentic, and developer-platform technology ecosystem and translate relevant changes into product implications, opportunities, and roadmap updates.

Product Areas

• Agentic Development Framework: Developer frameworks, tooling, and reusable capabilities for building and integrating agentic AI applications aligned with firm standards and patterns, including the agent harness and Harness Studio for developing, configuring, testing, and working with agents.
• Agentic Control Plane: Platform capabilities for governing and operating agentic AI applications at scale, including the MCP gateway, agent and tool registry, inventory, observability, and lifecycle management.

Required Qualifications

• Experience owning a technical platform, developer product, developer tooling, or infrastructure capability where primary users are software engineers or other technical practitioners.
• Prior hands-on software engineering or application development experience, with proficiency in at least one prominent programming language, preferably Python, and sufficient technical depth to engage credibly on APIs, frameworks, integration patterns, architecture, and engineering trade-offs.
• Strong understanding of modern AI/ML and Generative AI architectures, including familiarity with agentic AI applications and the developer lifecycle for building, integrating, deploying, governing, and operating them.
• Understanding of core technologies used in AI application development, including foundation models, APIs, agent frameworks, retrieval, tool integration, observability, and cloud and on-premises deployment patterns.
• Ability to understand and contribute to technical trade-offs involving architecture, APIs, interoperability, security, governance, scalability, reliability, performance, operational complexity, cost, and developer experience.
• Demonstrated ability to establish product vision and translate it into clear priorities, roadmaps, technical requirements, and delivery outcomes for a developer-facing platform.
• Strong consensus-building and influencing skills, including the ability to drive decisions across engineering leads, architects, platform teams, control partners, and other technology stakeholders without relying on direct authority.
• Excellent written and verbal communication skills, including the ability to translate complex technical concepts for application developers, engineering teams, senior technology leaders, control partners, and external technology partners.
• Ability to operate effectively in emerging product areas where requirements, technologies, architectural patterns, and stakeholder expectations are evolving.

Preferred Skills and Experience

• Experience with agentic AI frameworks, developer platforms, platform engineering, API products, observability, or AI governance and control-plane capabilities.
• Experience designing or owning developer experiences that include APIs, SDKs, frameworks, integrated development tooling, platform integrations, documentation, or self-service onboarding.
• Understanding of Responsible AI, information security, defense-in-depth, zero-trust, and control requirements relevant to deploying AI applications in a regulated enterprise.
• Experience evaluating third-party, open-source, and internally developed technology capabilities to support build-versus-buy decisions.
• Experience working in financial services or another large, global, regulated organization.

Tools and Technologies

• Python, Jira, PowerPoint, Excel

Location and Compensation

• Location: New York, NY (onsite)
• Salary: USD 155,000 - 215,000 per yearly

Minimum Experience and Education

• Minimum experience: 10 years
• Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience