VP, Generative AI, Backend 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 Generative AI, Backend Engineering 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.

We are seeking an experienced and hands-on engineering leader to design, build, and deliver scalable, production-grade platforms and applications, including the next generation of Generative AI-powered solutions.

The ideal candidate will bring deep expertise in one or both of two areas: backend/distributed systems engineering and Generative AI engineering. We are equally interested in strong backend engineers who have built complex, large-scale production systems and are excited to apply their expertise to Generative AI, as well as experienced AI engineers who bring strong software engineering fundamentals and have successfully built and operated distributed systems in production.

This role is ideal for a technical leader who enjoys solving complex engineering problems, remains hands-on with technology, and can take systems from architecture and implementation through production deployment and operation. You will work closely with business and technology partners to deliver highly scalable, reliable, and intelligent products in a fast-paced investment banking environment.

What you’ll do in the role:

• Lead the end-to-end design, development, and delivery of scalable backend and Generative AI solutions from concept through production deployment.
• Architect secure, resilient, high-performance distributed systems and services supporting enterprise applications and AI-powered capabilities.
• Design and build backend services, APIs, data and orchestration layers, and platforms that can reliably support Generative AI applications at enterprise scale.
• Provide hands-on technical leadership during architecture, solution design, implementation, code reviews, troubleshooting, and production support.
• Drive technical decision-making to ensure solutions are scalable, maintainable, performant, and aligned with enterprise engineering standards.
• Integrate Generative AI capabilities including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), intelligent agents, and related technologies into production applications where appropriate.
• Collaborate closely with product owners, business stakeholders, architects, AI engineers, and engineering teams to translate business requirements into high-quality technical solutions.
• Lead technical planning, estimation, execution, and delivery across multiple concurrent initiatives.
• Ensure systems are production-ready with appropriate monitoring, observability, testing, security, resiliency, performance, and operational support.
• Drive engineering best practices including CI/CD, automated testing, code quality, infrastructure automation, and, where applicable, MLOps.
• Evaluate emerging technologies across Generative AI and software engineering and recommend practical adoption where they improve products, delivery, or engineering productivity.
• Mentor engineers and promote engineering excellence through technical guidance, architecture and design reviews, code reviews, and knowledge sharing.

What you’ll bring to the role:

• 10+ years of software engineering experience designing, developing, and delivering complex production-grade systems in enterprise environments.
• Proven experience leading or collaborating with engineering teams and delivering complex technology initiatives in large enterprise environments.
• Strong hands-on software engineering and system design skills, with demonstrated experience building scalable, resilient, and highly available production systems.
• Strong programming skills in Python, Java, or another enterprise programming language, with the ability and willingness to work across technologies as needed.
• Strong experience developing distributed systems using technologies and patterns such as microservices, REST API…