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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Generative AI & Machine Learning Engineer - **Company:** Morgan Stanley - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $155,000.0 - $215,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, Cloud Computing, Cloud Engineering, Software Quality, Code Review, Computer Programming, Continuous Integration, DevOps, Distributed Systems, Github, Python (Programming Language), Machine Learning, Performance Tuning, Software Maintenance, Software Deployment, Software Engineering, User-Centered Design, Google Cloud, Large Language Models, Prompt Engineering, Generative AI, Containerization, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Machine Learning Operations, Virtual Agents, Restful APIs, Docker, Jenkins, Microservices - **Published:** August 4, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=48ef584643aa7bd1 ## About the Role * 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. * 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. Preferred Qualifications * Experience within Investment Banking, Capital Markets, or Financial Services technology. * Experience with Kubernetes, Docker, GitHub Actions, Jenkins, MLflow, or similar DevOps and MLOps tooling. * Familiarity with cloud platforms such as Azure, AWS, or Google Cloud ## Description 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 & Machine Learning 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., We are seeking an experienced and hands-on engineering leader specializing in Generative AI (GenAI), Large Language Models (LLMs), intelligent agents, and Machine Learning. This role is ideal for a technical leader who enjoys solving complex engineering problems, working closely with business and technology partners, and leading the end-to-end delivery of AI-powered 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 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. ## Related Videos - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) - [Accelerating GenAI Development: Harnessing Astra DB Vector Store and Langflow for LLM-Powered Apps](https://www.wearedevelopers.com/videos/966-accelerating-genai-development-harnessing-astra-db-vector-store-and-langflow-for-llm-powered-apps) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)