Agentic AI Engineer

Morgan Stanley • New York, NY

1d • $155,000 - $215,000

About The Position

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Agentic AI Engineer position at the Vice President level, which is part of the job family responsible for developing and maintaining software solutions that support business needs. Morgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals. Interested in joining a team that’s eager to create, innovate and make an impact on the world? Read on. Institutional Securities Technology (IST) develops and oversees the overall technology strategy and bespoke technology solutions to drive and enable the institutional businesses and enterprise-wide functions. IST’s ‘clients’ include Fixed Income, Equities, Commodities, Investment Banking, Research, Prime Brokerage and Global Capital Markets. Research Technology, part of IST, works uses agile delivery model. There are squads of 6-12, that are assigned projects. Each squad works with a Product Owner and focuses on the delivery of the required business features. We're seeking someone to join our Research technology team as a AI/Agentic AI Lead Engineer in ASD super department to expand and accelerate AI initiatives in the research department, focusing on building scalable, governed, and resilient GenAI and agentic solutions.

Requirements

• Ability to effectively manage multiple functions or guide junior staff and initiatives.
• Advanced understanding of business line and discipline with some knowledge of 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 that are business and regulatory driven.
• 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

Responsibilities

• Communicate regularly with product leads across the technology organization and discuss opportunities for improvement to 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.

Benefits

• Ample opportunity to move about the business for those who show passion and grit in their work.
• Attractive and comprehensive employee benefits and perks in the industry.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager