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The Core Engineering, Surveillance & Models-Software Engineering, Vice President, Dallas

Goldman Sachs
Dallas, USA
Executive · 5+ years experience
Discovered 1 weeks ago
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QUALIFICATIONS

  • A successful candidate will possess the following attributes:
  • A Bachelor's or Master's degree in Computer Science, Computer Engineering, or a similar field of study.
  • 5+ years professional software development experience
  • Expertise in Java and/or Python development.
  • Experience in automated testing and SDLC concepts.
  • The ability (and tenacity) to clearly express ideas and arguments in meetings and on paper.
  • Experience in some of the following is desired and can set you apart from other candidates:
  • Demonstrated experience or a strong interest in leveraging AI-assisted developer tools to enhance engineering productivity and accelerate software delivery.
  • Ability to critically evaluate AI‐generated outputs and enhance them to production‐grade quality.
  • Proven ability to critically evaluate AI-generated outputs and refine them to meet production-grade standards of quality, reliability, and maintainability.
  • Hands-on proficiency with AI coding assistants such as GitHub Copilot, Claude Code, and Devin to expedite code authoring, refactoring, and debugging across all phases of the Software Development Life Cycle (SDLC ).
  • Effective utilization of AI pair-programming tools to generate boilerplate code, unit tests, and technical documentation, enabling greater focus on architectural design and complex problem-solving.
  • Application of established prompt engineering best practices to elicit high-quality, context-aware code recommendations and reduce iteration cycles during development.
  • Practical integration of autonomous AI agents (e.g., Devin) for routine engineering tasks, including bug triage, dependency upgrades, and minor feature implementations, thereby freeing engineering bandwidth for higher-impact initiatives.
  • Adoption of AI-driven code review tools to proactively identify defects, security vulnerabilities, and performance bottlenecks earlier in the development cycle, strengthening overall quality gates.
  • Experience with:
  • API design and micro-services architecture, such as to create interconnected services
  • Cloud-based data platforms, such as Snowflake
  • Apache Spark and/or Hadoop
  • Data Lake or Lakehouse solutions
  • Relational databases
  • Knowledge of the financial industry and compliance or risk functions
  • Influencing and collaborating with stakeholders.

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