AI / ML Engineer

Role overview

This opportunity sits within the Technology division and is aligned to a Software Engineering III role at Director level. The position focuses on developing and supporting software capabilities that solve business problems, while contributing to the firm’s broader innovation agenda.

Morgan Stanley is a global financial services organization that helps governments, corporations, institutions, and individuals raise, manage, and deploy capital to meet their financial goals.

The role is part of a team working across Advanced Analytics, Machine Learning, and GenAI platforms, collaborating with colleagues in India and the US. The selected candidate will help design autonomous systems that can reason, call tools, and complete multi-step tasks using LLMs and reasoning models, while also creating calibration scoring and safeguards to improve agent accuracy. The work will feed into the cloud adoption and engineering roadmap, with an emphasis on scalable, agile, and resilient architecture and implementation. The role calls for someone who can operate independently in a fast-moving environment, share knowledge with teammates, and manage priorities across multiple global initiatives.

What you will do

• Contribute as a hands-on engineer helping build and launch AI agents at scale to support technology and business priorities.
• Assess modern ML and GenAI technologies and develop prototypes that strengthen the platform and architecture.
• Architect, build, and run distributed data pipelines that ingest, transform, store, and serve data in batch and real-time for AI agent use cases.

What the role requires

• At least 2 years of experience building GenAI solutions and supporting the design, architecture, development, and operational rollout of large-scale agent orchestration.
• Strong command of agent orchestration tools such as LangChain, LangGraph, CrewAI, and AutoGen for multi-agent workflows.
• Deep experience working with LLM APIs such as OpenAI, Anthropic, and AWS Bedrock, along with prompt engineering techniques including chain-of-thought and fine-tuning for agent behavior.
• Capability to build memory and context systems using vector databases such as Pinecone and Weaviate, as well as RAG pipelines.
• Ability to integrate external APIs as tools for agents, including function calling and handling malformed model responses.
• Advanced Python skills are mandatory; experience with FastAPI, Node.js, or Go is also relevant, along with standard use of Docker and Kubernetes for containerized deployment.
• Understanding of end-to-end machine learning lifecycles and production MLOps practices.
• Comfort working in a fast-paced, dynamic environment.
• Strong written and verbal communication skills.

Compensation and benefits

The expected base salary for this position is between USD 120,000 and USD 165,000 per year. Actual pay will be determined individually and may also include commission, incentive pay, discretionary bonuses, and other short- and long-term incentive programs, along with Morgan Stanley benefit offerings.

Employees and their families are supported through comprehensive benefits and perks, with opportunities to grow across the business for those who demonstrate initiative and resilience.

Equal opportunity and inclusion

Morgan Stanley is an equal opportunity employer and is committed to building a diverse workforce. Hiring, development, and advancement are based on skills and talent, within a culture that values inclusion, different backgrounds, and a wide range of perspectives.

Additional information

The role is based in New York, NY and is onsite. Morgan Stanley’s global office locations are available on its official corporate website. Further details about employment practices and equal opportunity information are also available through the company’s public pages.