Java Backend Engineer - Director - Software Engineering
Profile Description
We're seeking someone to join our Institutional Securities Technology (Prime Brokerage AND Institutional Equity) team as a Java Backend Engineer . for a strong Backend Java 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.
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.
This is Director position that develops and maintains software solutions that support business needs.
What you'll do in the role:
• 6+ years 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 will 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
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
- 6+ years of hands-on Java development experience
- Deep experience with Spring Boot, microservices, REST APIs, and messaging integrations such as 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
- Strong problem-solving ability and ability to learn new technologies quickly
- Interest in AI-assisted or agentic software development with hands-on LLM integration exposure
- Understanding of orchestrator/subagent patterns, tool or function calling, evaluation-driven iteration, and prompt engineering
- Python exposure for AI integration, scripting, or data pipelines
- Hands-on experience integrating OpenAI, Azure OpenAI, Anthropic, or equivalent LLMs into production backend systems
- Working knowledge of agentic AI frameworks such as LangChain, LangGraph, Spring AI, AutoGen, CrewAI, or Claude Agent SDK
- Ability to design multi-agent workflows, agent communication, and guardrails for autonomous systems
- Awareness of AI reliability concerns including hallucination mitigation, tracing, latency, and cost management
- Knowledge of RAG architecture and vector database concepts
- Financial services or investment banking domain experience
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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Parental & Family Support — Family support is extensive, with paid parental leave for all parents, adoption and fertility assistance, backup childcare, and eldercare resources. Feedback suggests these programs meaningfully enhance the overall package and help with retention.
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Healthcare Strength — Health coverage spans medical, dental, vision, mental‑health access, care navigation, and expert second opinions. Convenient primary care access and condition‑specific support reinforce the depth of healthcare coverage.
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Equity Value & Accessibility — Equity compensation and stock ownership are positioned as core motivators that encourage commitment and retention. Feedback suggests education and support are provided to help participants manage equity and related financial benefits.
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.
