Associate Full-Stack Engineer - AI-Driven Payments Platform

The Goldman Sachs Group; New York (NY); On-site; USD 115,000 - 180,000; Full time

Job summary

Goldman Sachs is seeking a Full Stack Engineer in New York to build mission-critical payment services on AWS and lead the adoption of AI-augmented development. You will design, code, and operate end-to-end solutions while mentoring others in AI-assisted engineering patterns.

You will drive modern SDLC practices, migrate legacy logic to cloud-native microservices, and collaborate across teams to deliver secure, scalable software.

Qualifications

• 4–6 years of professional software engineering experience (Associate level).
• Deep expertise in Java and the Spring Framework; Python for automation/AI.
• Strong experience with React and TypeScript frontend development.
• 5+ years with SQL (relational) and NoSQL databases like DynamoDB, Aurora PostgreSQL, Cassandra.
• Experience with MSK messaging and RESTful APIs/microservices architectures.
• AWS cloud-native experience: Lambda, ECS/EKS, S3, IAM, KMS, CloudFormation/CDK.
• Docker and Kubernetes orchestration; SecDevOps mindset.

Responsibilities

• Design and implement scalable full-stack applications on AWS using Java (Spring Boot) and Python.
• Lead AI-augmented engineering practices with tools like Copilot, Claude Code, Devin AI.
• Build responsive front-end components (React/TypeScript) and robust back-end APIs with multiple databases.
• Manage the SDLC with GitLab CI/CD, emphasizing automated tests and security scans.
• Refactor legacy payment logic into cloud-native microservices and mentor engineers.

Skills

Java & Spring

Python

React

TypeScript

SQL

NoSQL

MSK

RESTful APIs

Microservices

GitLab CI/CD

Tools

Docker

Kubernetes (EKS)

AWS CDK/CloudFormation

Git

Job description

Goldman Sachs is seeking a Full Stack Engineer in New York to build mission-critical payment services on AWS and lead the adoption of AI-augmented development. You will design, code, and operate end-to-end solutions while mentoring others in AI-assisted engineering patterns.

You will drive modern SDLC practices, migrate legacy logic to cloud-native microservices, and collaborate across teams to deliver secure, scalable software.