About The Position

Goldman Sachs is modernizing its payments platform as part of a broader strategy to digitize operations and provide financial services "as a Service." The payments platform is transforming premise-based infrastructure into nimble, reliable, and scalable services designed for the public cloud. This transformation requires uplifting and modernizing staff skillsets. We are seeking forward-thinking engineers with cloud engineering discipline and mastery of AI-augmented development to innovate 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 initiatives.

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.
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