VP, Generative AI & ML Platform Engineer

PowerToFly; New York (NY); On-site; USD 155,000 - 215,000; Full time

Job summary

Morgan Stanley is seeking an experienced Generative AI & Machine Learning Engineering leader at VP level to design, build, and ship AI-powered products for enterprise use. You will guide end-to-end delivery, mentor engineers, and collaborate closely with business units in a fast-paced investment banking environment.

The role demands hands-on expertise in GenAI, LLMs, RAG, and scalable architectures, with strong Python skills and cloud-native delivery.

Qualifications

• 10+ years of AI/ML and software engineering experience delivering production-grade AI solutions in enterprise environments.
• Proven experience leading engineering teams and delivering complex technology initiatives.
• Strong hands-on experience building production AI/ML applications with GenAI, LLMs and RAG.

Responsibilities

• Lead end-to-end design and delivery of enterprise AI/ML solutions from concept to production.
• Architect scalable AI platforms using LLMs, RAG, and intelligent agents.
• Provide hands-on technical leadership during solution design, reviews, and production support.
• Drive decision-making for scalable, secure, enterprise-grade engineering standards.
• Collaborate with product owners and stakeholders to translate requirements into technical solutions.
• Lead planning, estimation, sprints, and delivery across multiple initiatives.
• Ensure production readiness with monitoring, security, and operations support.
• Promote engineering best practices including CI/CD, testing, and MLOps.

Skills

Generative AI

LLMs

RAG

Python

Distributed systems

Cloud-native

MLOps

Leadership

Agile

OpenAI/Azure OpenAI

LangChain

Vector databases

Tools

Kubernetes

Docker

GitHub Actions

Jenkins

MLflow

LangGraph

Job description

Morgan Stanley is seeking an experienced Generative AI & Machine Learning Engineering leader at VP level to design, build, and ship AI-powered products for enterprise use. You will guide end-to-end delivery, mentor engineers, and collaborate closely with business units in a fast-paced investment banking environment.

The role demands hands-on expertise in GenAI, LLMs, RAG, and scalable architectures, with strong Python skills and cloud-native delivery.