VP , P5, Software Eng Mgr : Job Level - Vice President

Overview

Design and build AI-enabled tools, workflows, and agents that help program managers move typical project and program management activities from manual, document-heavy processes to AI-assisted operating models within Morgan Stanley's technology environment.

What you'll do

• Design, build, test, and maintain AI-enabled tools, workflows, and agents that help program managers automate or streamline common project and program management processes.
• Develop solutions using Claude Code, GitHub Copilot, AMP, and approved Morgan Stanley engineering platforms.
• Translate program management pain points into practical AI use cases, prototypes, reusable components, and production-ready solutions.
• Build AI-assisted capabilities for activities such as status report generation, RAID log analysis, dependency tracking, governance pack preparation, meeting note synthesis, action item extraction, milestone tracking, financial tracking support, and stakeholder communications.
• Create human-in-the-loop and human-on-the-loop workflows that improve efficiency while retaining appropriate oversight, review, and accountability.
• Apply sound software engineering practices, including version control, testing, peer review, secure coding, documentation, and maintainable design.
• Integrate AI solutions with existing delivery tooling where appropriate, including platforms used for project tracking, reporting, documentation, workflow management, or engineering delivery.
• Help assess the suitability, quality, reliability, and limitations of AI-generated outputs before they are introduced into program management workflows.
• Support the creation of reusable prompt patterns, agent workflows, reference implementations, and engineering standards for AI-enabled program management solutions.
• Produce clear technical documentation, user guidance, and support materials to help program managers adopt AI-enabled solutions confidently.
• Contribute to governance, risk, and control considerations for AI solutions, including appropriate review points, auditability, access controls, and data handling.

What you'll need

• Experience working within Morgan Stanley, with a strong understanding of the Firm's technology development environment, tooling, controls, and delivery expectations.
• Hands-on experience developing AI-enabled solutions using tools such as Claude Code, GitHub Copilot, AMP, or comparable AI-assisted engineering platforms.
• Strong software engineering capability, ideally with experience in Python, TypeScript, Java, or other relevant enterprise development languages.
• Experience building practical AI applications, such as agents, workflow automations, document generation tools, summarisation pipelines, retrieval-based applications, or decision-support assistants.
• Familiarity with prompt engineering, AI workflow design, model evaluation, structured outputs, testing AI-generated responses, and managing AI reliability risks.
• Good understanding of software delivery lifecycle practices, including requirements analysis, solution design, development, testing, deployment, documentation, and support.
• Ability to work with ambiguity and convert loosely defined business problems into structured technical solutions.
• Understanding of typical program management activities such as planning, RAID management, dependency tracking, governance reporting, financial tracking, status reporting, and steering committee preparation.
• Awareness of risk, control, data protection, and responsible AI considerations in a financial services environment.

Nice to have

• Prior experience in Morgan Stanley Technology or another highly controlled enterprise technology environment.
• Experience with internal developer platforms, CI/CD tooling, source control, secure engineering practices, and enterprise SDLC controls.
• Experience using AI coding assistants to accelerate development while maintaining appropriate code quality, review, and governance.
• Familiarity with program management tools and collaboration platforms such as Jira, Confluence, SharePoint, Teams, Power BI, Tableau, Excel, or related delivery reporting tools.
• Experience developing AI solutions that interact with documents, meeting notes, project plans, status reports, risk logs, or structured delivery data.
• Knowledge of retrieval augmented generation, agentic workflows, tool-calling patterns, structured prompting, evaluation frameworks, or AI guardrail implementation.
• Experience designing solutions that combine automation with human review, approval, exception handling, and escalation points.
• Understanding of technology risk, operational resilience, cybersecurity, controls, regulatory delivery, or large-scale transformation programs.
• Ability to create lightweight prototypes quickly and then harden successful concepts into reusable, supportable solutions.
• Curiosity, creativity, and a strong interest in helping program managers work more effectively through responsible use of AI.

Details

• Location: Bengaluru, India.
• The role is hands-on engineering and requires some project management experience (ideally).