Director - Applied AI

Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world. In the Legal & Compliance division, we assist the Firm in achieving its business objectives by facilitating and overseeing the Firm's management of legal, regulatory, and franchise risk.

We're seeking a Director - Applied AI to join our Non-Financial Risk team to design, build, and deploy AI-powered applications, agents, and plugins. These solutions will help Legal, Compliance, and Financial Crimes stakeholders manage legal, regulatory, and franchise risk and identify suspicious activity and potential financial crimes.

This is a Director level position within the NFR Data & Analytics team, which is responsible for designing and delivering AI-powered surveillance solutions and tools to help identify suspicious and/or illegal behaviors like money laundering, market manipulation, insider trading, unfair sales or trading practices and other financial crimes. The role will also deliver machine-assisted solutions that support the creation of Non-Financial Risk components, including processing regulatory rules, identifying policy gaps, determining primary and residual risks, and creating actionable controls for inclusion in testing programs.

What You'll Do In The Role

• Design and build high-performance AI applications leveraging Large Language Models (LLMs) and Agentic AI architecture, including multi-agent orchestration and planning, tool/function calling, Model Context Protocol (MCP) integrations, retrieval-augmented generation (RAG) over vector stores and knowledge graphs, short- and long-term memory and context management, structured outputs, guardrails, and human-in-the-loop controls.
• Build prompts, skills, agents, and tools, and package them as plugins for end-user platforms such as Microsoft 365 Copilot, OpenAI Enterprise, and Claude Enterprise.
• Create GenAI-based solutions to automate manual tasks and drive cost efficiency.
• Partner with technology and infrastructure teams to take AI solutions and plugins from prototype to production, including deployment, monitoring, and ongoing support.
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