Compliance Engineering, Software Engineer, Associate, Dallas

Job Description HOW YOU WILL FULFILL YOUR POTENTIAL

As a member of our team, you will:

• partner globally with sponsors, usersand engineering colleagues across multiple divisions to create end-to-end solutions,
• learn from experts
• leverage various technologies depending on the team including Java, Python, PySpark,SQL, Hadoop, Snowflake, Iceberg, Kafka, Kubernetes
• apply analytical and functional skills to design surveillance processes to identify risks
• be able to innovate and incubate new ideas
• havean opportunity to work on a broad range of problems, often dealing with large data sets,including real-time processing, messaging,workflow and UI/UX
• be involved inthe full life cycle; defining,designing, implementing, testing, deploying, and maintaining software acrossour products.

In addition, you will:

• Effectively use
  AI‑assisted software development tools
  (e.g., Git Hub Copilot, Devin, Claude Code, or equivalent) to improve developer productivity and reduce development cycle time.
• Apply AI tools to accelerate:
  • code generation and refactoring,
  • test creation and coverage improvement,
  • debugging, root‑cause analysis, and performance optimization.
• Use AI‑assisted reasoning to understand complex codebases, rapidly prototype solutions, and improve code quality while maintaining strong engineering standards.
• Partner with peers and reviewers to
  validate, harden, and product ionize AI‑generated outputs
  , ensuring correctness, security, maintainability, and regulatory compliance.
• Identify opportunities where AI tooling can reduce manual effort, minimize rework, and support faster, higher‑quality delivery to production.

A successful candidate will possess the following attributes:

Experience in some ofthe 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
  Git Hub 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.

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we…