AI Integration Software Engineer - Associate

Morgan Stanley•New York, NY

4d•$95,000 - $135,000

About The Position

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 Data & Analytics Engineering position at the Associate level, which is part of the job family responsible for providing specialist data analysis and expertise that drive decision-making and business insights as well as crafting data pipelines, implementing data models, and optimizing data processes for improved data accuracy and accessibility, including applying machine learning and AI-based techniques. This role is to build out the ISG GenAI & Data Analytics strategy, specifically working on the Chat With Your Data solution (DaiZy), integrating with Enterprise AI solutions and preparing datasets for GenAI usage. Candidates are expected to have hands-on data platform and LLM experience to design, build, and deploy scalable services and integrations for business-critical applications. Strong Python skills, production-ready coding standards, and effective collaboration in a client-facing consulting environment.

Requirements

3–5 years of software development or consulting experience.
Strong Python proficiency with at least one framework (FastAPI, Flask, or Django); working knowledge of Node.js/TypeScript.
Solid grasp of REST API design, microservices, auth, and service-to-service integration.
Experience with Git workflows, CI/CD, and automated testing.
Hands-on Snowflake experience (data migration, querying and app integration).
Proficiency integrating LLMs via hosted model APIs or enterprise AI platforms.
Strong debugging, communication, and problem-solving skills; able to work independently and within multidisciplinary teams.
Finance business understanding

Responsibilities

Design, build, and maintain backend services, REST APIs, and integrations using Python (FastAPI, Flask, or Django); some Node.js/TypeScript as needed.
Build distributed services in a microservices architecture with token-based auth and role-based access controls.
Integrate internal apps with third-party systems, external APIs, and Snowflake (data access, transformation, integration).
Develop LLM-powered features: model APIs, prompt workflows, structured outputs, and retrieval-based (RAG) applications.
Write clean, modular, secure code with unit, integration, and automated tests.
Participate in code reviews, Git workflows, and CI/CD pipelines.
Troubleshoot application, integration, data, and production issues.
Collaborate with architects, engineers, data teams, product owners, and clients; translate requirements into implementation plans and clear technical documentation.