Sr AI Engineer

Morgan Stanley; New York (NY); On-site; USD 150,000 - 215,000; Full time

Job summary

Morgan Stanley is seeking a Lead Software Engineer (VP) in the Technology division to drive GenAI‑based agent orchestration and scalable AI solutions. You’ll work with teams in the US and India to design robust architectures and shepherd multi‑agent workflows from prototype to production.

The role demands 6+ years in GenAI, strong Python and backend skills, and experience with LangChain, LangGraph, and AutoGen, plus containerized deployments with Docker and Kubernetes.

Qualifications

• 6+ years of experience building GenAI solutions and orchestrations at scale.
• Experience with multi-agent workflows and agent orchestration frameworks.
• Deep expertise in LLM APIs, prompt engineering and RAG pipelines.

Responsibilities

• Lead hands-on engineering to build and deploy AI agents at scale.
• Collaborate across divisions to align AI solutions and demonstrate POCs.
• Evaluate GenAI technologies and prototype scalable architectures.
• Design and operationalize distributed data flows for batch and real-time use by AI agents.

Skills

GenAI solutions

Agent orchestration

LangChain

LangGraph

AutoGen

LLM APIs

Prompt engineering

Vector databases

Pinecone

Weaviate

Function calling

Python

FastAPI

Docker

Kubernetes

Go

Node.js

Tools

LangChain

LangGraph

CrewAI

AutoGen

OpenAI

Anthropic

AWS Bedrock

Pinecone

Weaviate

Job 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 Lead Software 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.

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.

Interested in joining a team that’s eager to create, innovate and make an impact on the world? Read on.

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. The individual would be responsible for building autonomous systems that can reason, use tools, and complete multi-step tasks using LLMs/Reasoning models, build calibration scoring and guardrails for agent accuracy. The person would also be part of the overall cloud adoption and engineering roadmap and ensure scalable, agile and robust architecture and implementation. Additionally, should be able to work in a dynamic environment with limited or no supervision and should be able to knowledge share across other team members. Should be comfortable and manage time working with global team on multiple initiatives.

What you’ll do in the role:

• Sr Hand-On Engineer who acts as the catalyst in building and deploying AI Agents at scale to accelerate technology and business roadmaps
• Collaborate across multiple peer divisions to get alignment on AI Solutions demonstrate with POCs the \"Art of the possible\" and accelerate adoption
• Evaluate state-of-art Gen AI centric technologies and prototype solutions to improve our architecture and platform
• Design, Implement and Operationalize distributed, scalable, and reliable data flows that ingest, process, store, and access data at scale in batch / real-time used by AI Agents

What you’ll bring to the role:

• Experienced professional with 6+ years of experience working towards building GenAI solutions & supporting components design, architecture, development, and operationalization of agent orchestrations at scale.
• Agent Orchestration Frameworks: Mastery of frameworks like LangChain, LangGraph, CrewAI, and Microsoft's AutoGen to build multi-agent workflows.
• LLM Implementation: Deep expertise in LLM APIs (OpenAI, Anthropic, AWS Bedrock), prompt engineering (Chain-of-Thought), and fine-tuning for specific agentic behaviors.
• Memory & Context Management: Ability to implement complex memory systems, including vector databases (Pinecone, Weaviate) and Retrieval-Augmented Generation (RAG) pipelines.
• Tool-Calling & APIs: Proficiency in integrating external APIs as agent \"tools\", including function calling and error handling for malformed model outputs.
• Languages & Backend: Expert-level Python (mandatory), often paired with FastAPI, Node.js, or Go. Familiarity with Docker and Kubernetes for containerized deployment is standard.
• Ability to work in Fast paced and Dynamic environment.
• Good written and verbal communication skills

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals. We do it in a way that’s differentiated – and we’ve done that for 90 years. Our values – putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back – aren’t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences.

• We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry.
• There’s also ample opportunity to move about the business for those who show passion and grit in their work.

Expected base pay rates for the role will be between $150,000 and $215,000 per year at the commencement of employment. However, 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.

Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.

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.

For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.