Role overviewThe Enterprise AI organization is seeking a Technical Product Owner to shape and deliver firmwide infrastructure platform products for application developers building agentic AI applications. Application development and engineering teams are the primary customers, and the Product Owner will own the vision, strategy, roadmap, adoption, and evolution of a defined product area.
This role requires strong technical depth and credibility with software engineers and architects. The Product Owner will work closely with engineering leads, architects, application developers, control partners, and other technology stakeholders to understand developer needs, build consensus on technical direction and priorities, and translate that direction into an executable roadmap. The individual must be comfortable engaging in detailed technical discussions, understanding architectural choices and trade-offs, and communicating complex product and technical concepts effectively across engineering teams, senior technology leaders, control partners, and external technology partners.
Product areasAgentic Development Framework: Developer frameworks, tooling, and reusable capabilities for building and integrating agentic AI applications in alignment 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.
Primary responsibilities- Own the product vision, strategy, and roadmap for either the Agentic Development Framework or Agentic Control Plane.
- Develop a clear product direction by synthesizing the needs of application developers with input from engineering leads, architects, control partners, platform teams, and other technology stakeholders.
- Drive technical and product consensus across stakeholders with differing perspectives, turning complex technical choices and enterprise requirements 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 enable developers to build and operate applications effectively.
- Translate 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, build-versus-buy, and open-source-versus-vendor decisions in partnership with engineering and architecture.
- Drive common, reusable infrastructure capabilities and patterns rather than point solutions, enabling 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 adjustments.
Required skills and experience- Experience owning a technical platform, developer product, developer tooling, or infrastructure capability where the 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 with engineers and architects 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, such as 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, with 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 and supporting build-versus-buy decisions.
- Experience working in financial services or another large, global, regulated organization.
- Experience using product and delivery tools such as Jira and roadmapping tools, together with PowerPoint and Excel, to communicate priorities, status, and product direction.
Qualifications- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- Requires 10+ years in software development, software product management, or a related field.
WHAT YOU CAN EXPECT FROM MORGAN STANLEY: At Morgan Stanley, we raise, manage and allocate capital for our clients - helping them reach their goals. We do it in a way that's differentiated - and we've done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you'll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work.
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Expected base pay rates for the role will be between $155,000 and $215,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.
Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.
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