Agentic AI Engineer

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.

What you’ll do in the role:

• 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.

What you’ll bring to the role:

• 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

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.

To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices​ into your browser.

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.

For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.