Corporate Treasury, Payments Platform, Software Engineering, Associate, NY

Goldman Sachs•New York, NY

10h•$115,000 - $180,000•Onsite

About The Position

Goldman Sachs is modernizing its payments platform, transforming premise-based infrastructure into nimble, reliable, and scalable services designed for the public cloud. This transformation requires uplifting and modernizing staff skillsets. The company is seeking forward-thinking engineers with cloud engineering discipline and mastery of AI-augmented development to change software development practices.

Requirements

4-6 years of professional software engineering experience (Associate level).
Deep expertise in Java and the Spring Framework ecosystem.
Proficiency in Python for automation and AI integration.
Strong experience with modern JavaScript frameworks, specifically React and TypeScript.
5+ years working with SQL (relational) and experience with NoSQL databases like DynamoDB, Aurora Postgres, or Cassandra.
String experience with MSK.
Proven track record of designing and delivering RESTful APIs and microservices architectures.
2+ years of hands-on experience with AWS services, including Lambda, ECS/EKS, S3, IAM, KMS, and CloudFormation/CDK.
Strong knowledge of Docker and Kubernetes (EKS) for orchestrating distributed systems.
Experience implementing a SecDevOps mindset, including identity propagation and secure secret management in the cloud.
Demonstrated proficiency in using AI coding assistants (e.g., GitHub Copilot) and agentic AI (e.g., Claude Code, Devin AI) to improve velocity and code quality.
Ability to design structured prompts and workflows for AI agents to handle multi-step engineering tasks like unit test generation and documentation.
Strong ability to critically evaluate AI-generated outputs for correctness, security, and performance.

Nice To Haves

Familiarity with financial messaging standards (e.g., ISO 20022).
Contributions to open-source AI agent frameworks or internal AI-driven automation initiative.

Responsibilities

Design and implement scalable, secure full-stack applications using Java (Spring Boot) and Python, deployed as containerized (EKS) or server-less (Lambda) workloads on AWS.
Integrate AI tooling into daily workflows—using GitHub Copilot for real-time assistance, Claude Code for complex architectural reasoning, Devin AI for autonomous task execution and PR management and MCP.
Build responsive front-end components (React/TypeScript) and robust back-end APIs, ensuring seamless integration with relational (PostgreSQL) and non-relational (DynamoDB, MongoDB) databases.
Manage the complete lifecycle using GitLab CI/CD, emphasizing automated testing, security scanning, and rapid, high-quality value delivery.
Leverage AI agents to accelerate the migration of legacy payment logic into modern, cloud-native microservices.
Act as a technical authority, teaching fellow engineers how to effectively prompt, supervise, and validate AI-generated code to maintain enterprise-grade standards.