AI Java Lead Engineer _ Vice President _Software Engineering
We're seeking someone to join our Institutional Securities Technology (Prime Brokerage AND Institutional Equity) team as a Java Backend Engineer to build scalable, high-performance enterprise applications on a team that's adopting agentic AI workflows (built on frameworks like the Claude Agent SDK). This is fundamentally a backend engineering role — the bar is deep Java/Spring Boot craftsmanship and strong problem-solving. AI/agentic experience is crucial; we need someone who is aware & can quickly pick up orchestrator/subagent patterns & eval workflows.
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 Lead Software Engineer position at Vice President Level, which is part of the job family responsible for developing and maintains software solutions that support business needs.
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.
What you’ll do in the role:
- 8-16 Yrs. Of Hands-on Java development.
- Deep Spring Boot, microservices, REST APIs, messaging integrations (Kafka, JMS, RabbitMQ).
- Strong SQL, concurrency & distributed systems design
CI/CD, DevOps, production observability. - Experience in performance tuning and scalability improvements.
- Demonstrated strong problem-solving ability and comfort learning new technologies quickly
What you’ll bring to the role:
- Genuine interest in AI-assisted / agentic software development, with basic hands-on exposure (personal projects, POCs, or production) to LLM-integrated systems — e.g., calling OpenAI/Azure OpenAI/Anthropic APIs, or using tools like GitHub Copilot / Claude Code in a substantial way.
- Ability to grasp and reason about agentic concepts: orchestrator/subagent patterns, tool/function calling, eval-driven iteration ("hill climbing"), and basic prompt engineering.
- Python exposure for AI integration, scripting, or data pipeline use cases.
- Hands-on experience integrating LLMs into production backend systems (OpenAI, Azure OpenAI, Anthropic, or equivalent).
- Working knowledge of agentic AI frameworks — LangChain, LangGraph, Spring AI, AutoGen, CrewAI, or Claude Agent SDK — including agent memory, tool calling, and multi-step reasoning loops.
- Ability to design multi-agent workflows: orchestrator/subagent patterns, agent-to-agent communication, and guardrails for autonomous systems.
- Awareness of AI system reliability concerns: hallucination mitigation, observability (tracing agent runs), latency, and cost management.
- Curiosity and self-driven experimentation with emerging agentic patterns (ReAct, Chain-of-Thought, reflection loops, human-in-the-loop gates).
- RAG architecture and Vector Database concepts.
- Financial Services or Investment Banking domain experience.
- At least 6 years' relevant experience would generally be expected to find the skills required for this role.
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.
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.
Skills Required
- Hands-on Java development experience
- Deep experience with Spring Boot, microservices, REST APIs, and messaging integrations
- Experience with Kafka, JMS, or RabbitMQ
- Strong SQL, concurrency, and distributed systems design skills
- Experience with CI/CD, DevOps, and production observability
- Experience with performance tuning and scalability improvements
- At least 6 years of relevant experience
- Basic hands-on exposure to AI-assisted or agentic software development
- Experience integrating LLMs into production backend systems using OpenAI, Azure OpenAI, Anthropic, or equivalent
- Working knowledge of agentic AI frameworks such as LangChain, LangGraph, Spring AI, AutoGen, CrewAI, or Claude Agent SDK
- Ability to design multi-agent workflows, orchestrator/subagent patterns, agent communication, and guardrails
- Understanding of AI reliability concerns, including hallucination mitigation, tracing, latency, and cost management
- Python exposure for AI integration, scripting, or data pipeline use cases
- Knowledge of RAG architecture and vector database concepts
- Financial services or investment banking domain experience
- Understanding of prompt engineering, ReAct, reflection loops, and human-in-the-loop controls
Morgan Stanley Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Morgan Stanley and has not been reviewed or approved by Morgan Stanley.
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Healthcare Strength — Health coverage is characterized as comprehensive, with medical, dental, vision, and added supports like One Medical and mental-health sessions. Feedback suggests the overall package is strong to excellent for a large financial-services employer.
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Retirement Support — Retirement programs include a 401(k) with company matching and related financial benefits. These features are frequently highlighted as part of a broad, competitive package.
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Parental & Family Support — Family benefits are noted for generous paid parental leave, fertility support, and caregiver leave. Feedback suggests these offerings stand out as a strength within the package.
Morgan Stanley Insights
What We Do
Morgan Stanley mobilizes capital to help governments, corporations, institutions and individuals around the world achieve their financial goals. For over 85 years, the firm’s reputation for using innovative thinking to solve complex problems has been well earned and rarely matched. A consistent industry leader throughout decades of dramatic change in modern finance, Morgan Stanley will continue to break new ground in advising, serving and providing new opportunities for its clients. Morgan Stanley is committed to maintaining the first-class service and high standard of excellence that have always defined the firm. At its foundation are five core values — putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back — that guide its more than 60,000 employees in 1,200 offices across 41 countries.
