AI Engineer

Relha LLC; New York (NY); On-site; USD 120,000 - 165,000; Full time

Job summary

Morgan Stanley, in its Technology division, seeks a Software Engineering III (Director level) to join the Advanced Analytics, Machine Learning and Gen AI Platform teams across India & US. Build autonomous AI Agents, design scalable data flows, and ensure robust architecture while collaborating with global teams.

You will work in a fast-paced environment, implement multi-agent workflows, and leverage frameworks like LangChain, LangGraph, CrewAI, and AutoGen, using Python, FastAPI, Docker, and

Qualifications

• 2+ years of experience building GenAI solutions and agent orchestration at scale.
• Mastery of agent orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen).
• Deep experience with LLM APIs (OpenAI, Anthropic, AWS Bedrock) and prompt engineering.
• Memory systems and vector stores (Pinecone, Weaviate) and RAG pipelines.
• Proficient in integrating external APIs as agent tools with function calling/error handling.
• Expert Python; familiarity with FastAPI, Node.js or Go; Docker/Kubernetes experience.

Responsibilities

• Hands-On Engineer acting as catalyst to build and deploy AI Agents at scale.
• Evaluate GenAI technologies and prototype solutions to improve architecture.
• Design, implement, and operationalize scalable data flows for AI agents.

Skills

GenAI software engineering

Agent orchestration

LLM integration & prompt engineering

Memory & context management

Tool-calling & API integration

Python programming

FastAPI / Node.js / Go

Docker & Kubernetes

Tools

LangChain

LangGraph

CrewAI

AutoGen (Microsoft)

OpenAI API

Anthropic API

AWS Bedrock

Pinecone

Weaviate

Retrieval-Augmented Generation

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 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.

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:

• Hands-On Engineer who acts as the catalyst in building and deploying AI Agents at scale to accelerate technology and business roadmaps
• 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 2+ 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 $120,000 and $165,000 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.

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.

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