GenAI & Data Analytics Engineer | Python & LLMs

Morgan Stanley; New York (NY); On-site; USD 95,000 - 135,000; Full time

Job summary

Morgan Stanley is seeking a Data & Analytics Engineer (Associate) to design, build, and deploy scalable data and AI-enabled services. You will craft data pipelines, models, and ML-aware data integrations while collaborating with clients and product teams.

The role emphasizes Python backend development, REST APIs, and Snowflake data access, with production-ready coding standards and strong cross-functional communication in a client-facing setting.

Qualifications

• 3-5 years of software development or consulting experience.
• Strong Python proficiency with one framework (FastAPI, Flask, or Django).
• Working knowledge of Node.js/TypeScript.
• Solid REST API design and microservices experience.
• Git workflows, CI/CD, and automated testing experience.
• Hands-on Snowflake experience for data tasks.
• Ability to integrate LLMs via APIs and AI platforms.
• Strong debugging, communication, and problem-solving skills.

Responsibilities

• Design, build, and maintain backend services, REST APIs, and integrations using Python.
• Build distributed services in a microservices architecture with token-based auth and RBAC.
• Integrate internal apps with third-party systems and Snowflake.
• Develop LLM-powered features, model APIs, prompts, and retrieval-based apps.
• Write clean, modular, secure code with tests; participate in CI/CD and code reviews.
• Troubleshoot production issues across application, data, and integrations.
• Collaborate with architects, engineers, data teams, product owners, and clients; document requirements.

Skills

Python

Frameworks (FastAPI/Flask/Django)

Node.js/TypeScript

REST API design

Microservices

Auth & RBAC

Git workflows

CI/CD

Automated testing

Snowflake

LLMs integration

Debugging

Communication

Finance knowledge

Tools

Snowflake

Job description

Morgan Stanley is seeking a Data & Analytics Engineer (Associate) to design, build, and deploy scalable data and AI-enabled services. You will craft data pipelines, models, and ML-aware data integrations while collaborating with clients and product teams.

The role emphasizes Python backend development, REST APIs, and Snowflake data access, with production-ready coding standards and strong cross-functional communication in a client-facing setting.