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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI / ML Engineer - **Company:** Morgan Stanley - **Location:** New York, NY, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Distributed Data Store, Python (Programming Language), Software Engineering, Large Language Models, Multi-Agent Systems, Prompt Engineering, Fastapi, Build Management, AI Platforms, Machine Learning Operations, Data Pipelines, Docker - **Published:** August 8, 2026 - **Apply:** https://us.experteer.com/career/view-jobs/ai-ml-engineer-new-york-ny-usa-58853618 ## About the Role Experteer Overview In this Software Engineering III role within Morgan Stanley's Technology division, you will lead and hands-on develop AI-powered agents at scale. You'll collaborate with Advanced Analytics and Gen AI Platform teams across global settings to enable autonomous reasoning and tool usage. You'll help design scalable data pipelines and cloud-aligned architecture, balancing speed with reliability. This position offers meaningful impact through shaping AI-enabled capabilities that advance business roadmaps and technology strategy. Compensation / Benefits * Build and deploy AI agents at scale to accelerate technology and business roadmaps * Evaluate state-of-the-art ML/Gen AI technologies and prototype solutions * Design, implement and operationalize distributed data flows for batch/real-time AI agent use cases Tasks * 2+ years of GenAI solution development and agent orchestration at scale * Proficiency with agent orchestration frameworks (LangChain, LangGraph, CrewAI, aaaaaa AI * Deep expertise in LLM APIs (OpenAI, Anthropic, AWS Bedrock) and prompt engineering * Memory and context management with vector databases (Pinecone, Weaviate) and RAG pipelines * Ability to integrate external APIs as agent tools with error handling * Expert-level Python; experience with FastAPI; familiarity with Docker and Kubernetes * Understanding of end-to-end ML lifecycle and MLOps * Strong written and verbal communication skills Key requirements * comprehensive employee benefits and perks * global offices and collaboration across regions * inclusive culture and diversity * opportunity for growth and internal mobility * supportive work-life environment * competitive compensation package ## Description Experteer Overview In this Software Engineering III role within Morgan Stanley's Technology division, you will lead and hands-on develop AI-powered agents at scale. You'll collaborate with Advanced Analytics and Gen AI Platform teams across global settings to enable autonomous reasoning and tool usage. You'll help design scalable data pipelines and cloud-aligned architecture, balancing speed with reliability. This position offers meaningful impact through shaping AI-enabled capabilities that advance business roadmaps and technology strategy. Compensation / Benefits * Build and deploy AI agents at scale to accelerate technology and business roadmaps * Evaluate state-of-the-art ML/Gen AI technologies and prototype solutions * Design, implement and operationalize distributed data flows for batch/real-time AI agent use cases Tasks * 2+ years of GenAI solution development and agent orchestration at scale * Proficiency with agent orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen) * Deep expertise in LLM APIs (OpenAI, Anthropic, AWS Bedrock) and prompt engineering * Memory and context management with vector databases (Pinecone, Weaviate) and RAG pipelines * Ability to integrate external APIs as agent tools with error handling * Expert-level Python; experience with FastAPI; familiarity with Docker and Kubernetes * Understanding of end-to-end ML lifecycle and MLOps * Strong written and verbal communication skills Key requirements * comprehensive employee benefits and perks * global offices and collaboration across regions * inclusive culture and diversity * opportunity for growth and internal mobility * supportive work-life environment * competitive compensation package ## Related Videos - [This App Reached 10,000 Users in One Week. 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