AI / ML Engineer

About the role

This is a Software Engineering III position at the Director 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.

Responsibilities

• Partner with the Advanced Analytics, Machine learning and Gen AI Platform team(s), across multiple project areas, and work in collaboration with team(s) in India & US.
• Build autonomous systems that can reason, use tools, and complete multi-step tasks using LLMs/Reasoning models.
• Build calibration scoring and guardrails for agent accuracy.
• Part of the overall cloud adoption and engineering roadmap and ensure scalable, agile and robust architecture and implementation.
• Work in a dynamic environment with limited or no supervision and share knowledge across other team members.
• Manage time working with global teams on multiple initiatives.

Qualifications

• Experienced professional with 2+ years of experience working towards building GenAI solutions & supporting components design, architecture, development, and operationalization of agent orchestrations at scale.
• Mastery of frameworks like LangChain, LangGraph, CrewAI, and Microsoft's AutoGen to build multi-agent workflows.
• Deep expertise in LLM APIs (OpenAI, Anthropic, AWS Bedrock), prompt engineering (Chain-of-Thought), and fine-tuning for specific agentic behaviors.
• Ability to implement complex memory systems, including vector databases (Pinecone, Weaviate) and Retrieval-Augmented Generation (RAG) pipelines.
• Proficiency in integrating external APIs as agent tools, including function calling and error handling for malformed model outputs.
• Expert-level Python (mandatory), often paired with FastAPI, Node.js, or Go. Familiarity with Docker and Kubernetes for containerized deployment is standard.
• Understanding of applied Machine Learning (End-to-End) Lifecycle and Operationalizing ML models in Production (MLOps).
• Comfortable working in fast-paced and dynamic environments.
• Good written and verbal communication skills.

Skills

• Experience with GenAI solutions and supporting components design, architecture, development, and operationalization of agent orchestrations at scale.
• Knowledge of frameworks like LangChain, LangGraph, CrewAI, and Microsoft's AutoGen.
• Expertise in LLM APIs (OpenAI, Anthropic, AWS Bedrock).
• Prompt engineering (Chain-of-Thought) and fine-tuning for specific agentic behaviors.
• Ability to implement complex memory systems, including vector databases (Pinecone, Weaviate) and Retrieval-Augmented Generation (RAG) pipelines.
• Proficiency in integrating external APIs as agent tools, including function calling and error handling for malformed model outputs.
• Expert-level Python (mandatory), often paired with FastAPI, Node.js, or Go.
• Familiarity with Docker and Kubernetes for containerized deployment.
• Understanding of applied Machine Learning (End-to-End) Lifecycle and Operationalizing ML models in Production (MLOps).
• Comfortable working in fast-paced and dynamic environments.
• Good written and verbal communication skills.

Benefits

• Base pay range: $120,000 - $165,000 per year at the commencement of employment.
• Comprehensive employee benefits and perks.
• Opportunity to move about the business for those who show passion and grit in their work.

Pay

• Base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.

Schedule

• Flexible schedule to accommodate global team dynamics.

Company Information

Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents. Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.