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

The Core Engineering

The Core Engineering builds and operates the platforms applications data solutions models and analytics that power critical processes for The Core divisions of the firm (e.g. Risk responsible for the risk profile of firm activities; Controllers responsible for the financial control and reporting obligations; Compliance responsible for the firms compliance regulatory and reputational risks; Corporate Treasury responsible for the firms liquidity funding balance sheet etc.; and Human Capital Management responsible for attracting developing and managing a global workforce). A centralized engineering structure in support of The Core enables a common platform model and operating framework that promotes consistent governance and scalable solutions leveraging cloud AI and machine learning for innovation and efficiency. The Core Engineerings 2000 engineers and strats deliver engineering data analytics and quantitative capabilities within six business units:

• Metrics & Analytics Platforms: responsible for the measurement and management of the firms risk capital and liquidity for The Core functions

• The Core Strats: responsible for the development and implementation of models and other quantitative methodologies including the accuracy and attribution of modeled metrics

• Financials & Reporting: responsible for facilitating the production of the firms financials and a wide range of reporting functions

• Non-Financial Risk & Controls: responsible for non-financial risk and control processes

• Enterprise Platforms: responsible for platforms and applications that support critical operational processes across The Core such as payments people processes and procurement

• Shared Services: responsible for driving the adoption of consistent engineering strategy including data platforms cloud and AI enablement as well as the management of technology risk

HOW YOU WILL FULFILL YOUR POTENTIAL

As a member of our team you will:

• partner globally with sponsorsusersand engineering colleagues across multiple divisions to create end-to-end solutions
• learn from experts
• leverage varioustechnologies depending on the teamincluding Java Python PySparkSQL 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 setsincluding real-time processing messagingworkflow and UI/UX
• be involved inthe full life cycle; definingdesigning implementing testing deploying and maintaining software acrossour products.

AIAssisted Engineering & Productivity

In addition you will:

• Effectively useAIassisted software development tools(e.g. GitHub 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 rootcause analysis and performance optimization.
• Use AIassisted reasoning to understand complex codebases rapidly prototype solutions and improve code quality while maintaining strong engineering standards.
• Partner with peers and reviewers tovalidate harden and productionize AIgenerated outputs ensuring correctness security maintainability and regulatory compliance.
• Identify opportunities where AI tooling can reduce manual effort minimize rework and support faster higherquality delivery to production.

QUALIFICATIONS

A successful candidate will possess the followingattributes:

1. A Bachelors or Masters degreein Computer Science Computer Engineering or a similar field of study.
2. 5 years professionalsoftware development experience
3. Expertise in Java and/or Python development.
4. Experience inautomated testingandSDLC concepts.
5. The ability (and tenacity) to clearly express ideas and arguments in meetings and on paper.

Experience in some ofthe following is desired and can set you apart from other candidates:

• Demonstrated experience or a strong interest in leveragingAI-assisted developer toolsto enhance engineering productivity and accelerate software delivery.
• Ability to critically evaluateAIgenerated outputsand enhance them to productiongrade quality.
• Proven ability to critically evaluateAI-generated outputsand refine them to meet production-grade standards of quality reliability and maintainability.
• Hands-on proficiency with AI coding assistants such asGitHub CopilotClaude Code andDevinto 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 establishedprompt engineeringbest practices to elicit high-quality context-aware code recommendations and reduce iteration cycles during development.
• Practical integration of autonomousAI agents ()for routine engineering tasks including bug triage dependency upgrades and minor feature implementations thereby freeing engineering bandwidth for higher-impact initiatives.
• Adoptionof AI-driven code reviewtools 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
  • Influencingand collaborating with stakeholders.