Agentic AI Engineer

About the Role

This is a Vice President-level Agentic AI Engineer position within Institutional Securities Technology (IST). IST develops and oversees the overall technology strategy and bespoke solutions to drive and enable the institutional businesses and enterprise-wide functions, including Fixed Income, Equities, Commodities, Investment Banking, Research, Prime Brokerage, and Global Capital Markets. As part of Research Technology, you will join an agile team focused on expanding and accelerating AI initiatives, building scalable, governed, and resilient GenAI and agentic solutions.

Responsibilities

• Communicate regularly with product leads across the technology organization to discuss opportunities for improving existing and future technology solutions.
• Partner with business stakeholders and the GenAI Infrastructure Lead to identify and prioritize high-value Research AI and agentic AI use cases.
• Translate strategic business objectives into clear AI initiatives, delivery plans, and measurable outcomes.
• Lead rapid prototyping to test ideas, validate technical feasibility, and demonstrate business value quickly.
• Design, build, and deploy scalable, production-ready GenAI and agentic AI solutions with engineering teams.
• Collaborate with engineering leads to integrate AI capabilities into existing applications and workflows.
• Work with enterprise infrastructure and platform teams to define the architecture, services, and controls required for AI solutions.
• Ensure solutions meet enterprise standards for scalability, reliability, security, observability, and governance.
• Provide hands-on technical leadership across areas such as LLMs, RAG, agent orchestration, tool integration, and workflow automation.
• Advise business stakeholders on technical options, limitations, risks, costs, and implementation trade-offs.
• Coordinate across business, application-development, infrastructure, data, security, and governance teams.

Requirements

• Ability to effectively manage multiple functions or guide junior staff and initiatives.
• Advanced understanding of business line and discipline with knowledge of the competitive environment and other disciplines.
• Develop scalable solutions using Python and Java; write optimized, clean, production-grade code.
• Build systems that comply with regulatory standards.
• Influence beyond immediate teams to shape engineering standards and governance models.
• Engage in multi-year, high-visibility programs driven by business and regulatory needs.

Qualifications

• Hands-on experience leveraging Generative AI, coding assistants, and LLMs to improve software development and build AI-native applications.
• Experience designing, developing, deploying, and integrating MCP servers with AI agents and enterprise applications.
• Familiarity with vector databases and semantic search technologies, including platforms such as MongoDB, Redis, or similar vector stores.
• Experience with containers, pipelines, Linux, and shell scripting.
• Hands-on experience with AI agent orchestration frameworks such as LangChain/LangGraph, Claude Agent SDK, OpenAI Agents SDK, or equivalent frameworks.
• Utilize generative coding assistants and LLMs embedded into applications.
• Employ enterprise-grade DevOps, CI/CD, and observability tools.
• Excellent analytical, communication, and stakeholder management skills, with the ability to collaborate effectively across engineering, product, architecture, security, and business teams.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related discipline.

Benefits

Morgan Stanley offers some of the most attractive and comprehensive employee benefits and perks in the industry, supporting employees and their families at every point along their work-life journey. There’s also ample opportunity to move about the business for those who show passion and grit in their work.

Pay

Expected base pay rates for the role will be between $155,000 and $215,000 per year at the commencement of employment. Base pay is determined on an individualized basis and is only part of the total compensation package, which may also include commission earnings, incentive compensation, discretionary bonuses, other short- and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.