Generative AI & Machine Learning 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. 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.

Technology works as a strategic partner with Morgan Stanley business units and the world's leading technology companies to redefine how we do business in ever more global, complex, and dynamic financial markets. Our insights, applications, and infrastructure give a competitive edge to clients' businesses—and to our own.

About the Team

The Investment Banking and Global Capital Markets Technology is a globally distributed but close-knit team based in NY, LN, Mumbai, Bengaluru, and Pune. We are a highly innovative team that works in small groups that learn, grow, and succeed together. We follow Agile development practices to deliver high-quality solutions that delight our customers. As a member of the team, you will interact with others who are genuine and want you to succeed. Your talent, experience, and voice are valued and will make a difference.

Responsibilities

• Lead the end-to-end design, development, and delivery of enterprise AI and machine learning solutions from concept through production deployment.
• Architect scalable, secure, and resilient AI platforms leveraging LLMs, Retrieval-Augmented Generation (RAG), intelligent agents, and modern machine learning techniques.
• Provide hands-on technical leadership during solution design, implementation, code reviews, and production support.
• Drive technical decision-making to ensure solutions are scalable, maintainable, and aligned with enterprise engineering standards.
• Collaborate closely with product owners, business stakeholders, architects, and engineering teams to translate business requirements into high-quality technical solutions.
• Lead technical planning, estimation, sprint execution, and delivery across multiple concurrent initiatives.
• Ensure AI solutions are production-ready with appropriate monitoring, observability, testing, security, and operational support.
• Drive engineering best practices including CI/CD, automated testing, code quality, infrastructure automation, and MLOps.
• Evaluate emerging AI technologies and recommend practical adoption where they improve delivery or engineering productivity.
• Mentor engineers and promote engineering excellence through technical guidance, design reviews, and knowledge sharing.

Requirements

• 10+ years of AI/ML and software engineering experience, with a proven track record of designing, developing, and delivering production-grade AI solutions in enterprise environments.
• Proven experience leading engineering teams and delivering complex technology initiatives in large enterprise environments.
• Strong hands-on experience developing production-grade AI and machine learning applications.
• Deep experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and agent-based architectures.
• Strong programming skills in Python, with experience in Java or another enterprise programming language preferred.
• Experience developing distributed systems using microservices, REST APIs, containerization, and cloud-native architectures.
• Experience deploying AI applications using modern MLOps and DevOps practices.
• Strong understanding of software engineering fundamentals including system design, scalability, resiliency, testing, and performance optimization.
• Excellent communication skills with the ability to lead technical discussions across engineering and business teams.
• Experience working in Agile software development environments.

Skills

• Experience with OpenAI, Azure OpenAI, LangChain, LangGraph, or similar AI frameworks.
• Experience with vector databases and Retrieval-Augmented Generation (RAG) architectures.
• Experience building AI copilots, workflow automation, or agentic AI applications.
• Experience within Investment Banking, Capital Markets, or Financial Services technology (preferred).
• Experience with Kubernetes, Docker, GitHub Actions, Jenkins, MLflow, or similar DevOps and MLOps tooling (preferred).
• Familiarity with cloud platforms such as Azure, AWS, or Google Cloud (preferred).

Benefits

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.

Pay

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.