Compliance Engineering - Surveillance & Models Eng - Vice President - Bengaluru
On-siteBengaluru, Karnataka, India
Job Summary
Partner globally with sponsors and engineering colleagues to create end-to-end solutions that prevent, detect, and mitigate regulatory and reputational risk. Lead and coach teams while defining, designing, implementing, testing, and maintaining software across the full life cycle using Java, JavaScript, TypeScript, React, and Kafka. Leverage AI-assisted tools to accelerate code generation, refactoring, test creation, and debugging, then validate and harden AI-generated outputs for production-grade quality and compliance. Work with large data sets on real-time processing, messaging, and workflow systems while collaborating with stakeholders to influence product direction.
Required Qualifications
- 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 development
- Experience in automated testing and SDLC concepts
- The ability (and tenacity) to clearly express ideas and arguments in meetings and on paper
Desired Qualifications
- 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: UI/UX development
- API design, such as to create interconnected services
- message buses or real time processing
- relational databases
- knowledge of the financial industry and compliance or risk functions
- influencing and collaborating with stakeholders
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