below marketmost similar roles pay hereabove market
This role pays less than
55%
of similar roles. Most pay
$159,102–$235,750
— the blue band above.
At the midpoint, this role pays about
$185k
versus about
$197k
for comparable roles.
Based on 240 similar postings.
Employer
About Morgan Stanley
Morgan Stanley is a global financial services firm providing investment banking, securities, wealth management, and investment management services to corporations, governments, institutions, and individuals. Industry: Investment Banking & Financial Services
Morgan Stanley currently has
41 open roles
on FindRole.
Listed pay typically runs
$154,000–$215,000
across 35 roles with salary data.
The VP, Generative AI, Backend Engineer joins the Technology division to design, build, and deliver scalable, production-grade platforms and applications. This role involves leading the end-to-end development of backend and Generative AI solutions, including architecting secure, high-performance distributed systems and orchestration layers. The engineer will integrate Large Language Models, Retrieval-Augmented Generation, intelligent agents, and vector databases into production environments. Key responsibilities include providing hands-on technical leadership for architecture, code reviews, and troubleshooting while ensuring systems meet enterprise standards for monitoring, security, and resiliency. Required skills include proficiency in Python or Java, experience with microservices, REST APIs, and containerization, and knowledge of CI/CD and MLOps. The position addresses the technical challenge of deploying reliable, intelligent products within a fast-paced investment banking environment.
Lead the end-to-end design, development, and delivery of scalable backend and Generative AI solutions.
Architect secure, high-performance distributed systems and services for enterprise applications.
Build backend services, APIs, and orchestration layers to support Generative AI at scale.
Provide hands-on technical leadership for architecture, code reviews, troubleshooting, and production support.
Integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and intelligent agents into production.
Drive engineering best practices including CI/CD, automated testing, infrastructure automation, and MLOps.
Mentor engineers through technical guidance, architecture reviews, and knowledge sharing.
Evaluate and recommend emerging technologies to improve product delivery and engineering productivity.
What we're looking for
10+ years of software engineering experience designing and delivering complex production-grade systems in enterprise environments.
Proven experience leading or collaborating with engineering teams to deliver complex technology initiatives in large enterprise environments.
Strong hands-on software engineering and system design skills for building scalable, resilient, and highly available production systems.
Strong programming skills in Python, Java, or another enterprise programming language.
Experience developing distributed systems using microservices, REST APIs, event-driven architectures, containerization, caching, messaging, and cloud-native architectures.
Demonstrated experience taking complex systems into production, including scalability, resiliency, performance optimization, monitoring, observability, testing, security, and operational support.
Strong understanding of modern software engineering practices including CI/CD, automated testing, code quality, infrastructure automation, and DevOps.
Experience with Generative AI/ML technologies or demonstrated ability to develop expertise in building production-grade Generative AI systems.
Generative AI
LLM
Python
Vertex AI
GCP
LangChain
RAG
Prompt Engineering
FastAPI
Flask
REST APIs
BigQuery ML
Cloud Run
MLOps
CI/CD
NLP
Transformers
Java
C++
Linux
Snowflake
Hadoop
AWS
Generative AI
LLM
Vertex AI
GCP
Python
LangChain
RAG
Prompt Engineering
Java
C++
Flask
Spring
REST API
BigQuery ML
Cloud Run
MLOps
CI/CD
NLP
Transformers
LoRA
PEFT
Linux
Snowflake
Hadoop
AWS