Director, Software Engineering (AI Platform Development) - job 3 of 20

As the Director of Software Engineering at Visa, you will be responsible for leading strategic initiatives within the Payment Fraud Disruption team. This includes designing and developing machine learning platforms, driving excellence in engineering practices, and collaborating with product teams to influence product strategy. You'll also nurture your multi-disciplinary team, ensuring they thrive in a culture of ownership and accountability.

To succeed as the Director of Software Engineering at Visa, a strong engineering background is essential, along with proven leadership experience. You should possess expertise in machine learning, software development, and engineering practices, complemented by experience in the payments industry or related fields. Additionally, skills in partnership building and strategic thinking are crucial for influencing product roadmaps.

The Director of Software Engineering at Visa can enjoy a flexible hybrid work model, where you alternate between working remotely and in the office. You’ll be expected to work from the office three set days a week, depending on business needs, allowing for a balance of collaboration and remote productivity.

In the role of Director of Software Engineering at Visa, you will have a significant impact on shaping the future of fraud prevention within Visa's payment systems. By leading the Payment Fraud Disruption team, you will design robust systems that enhance security and reliability, directly contributing to the integrity and trustworthiness of Visa’s overall payment solutions.

Preparing for a leadership role such as the Director of Software Engineering at Visa involves developing both technical and soft skills. Focus on building a strong foundation in machine learning and software engineering while also honing your leadership abilities, such as mentoring, strategic thinking, and effective communication. Staying updated on industry trends will also be beneficial.

When answering, highlight specific projects or platforms you’ve worked on, explaining your role and the outcomes achieved. Discuss the challenges faced, how you overcame them, and the technologies used. This showcases your expertise in ML frameworks and candidate’s problem-solving skills.

Focus on discussing methodologies you implement for code reviews, testing, and CI/CD processes. Share examples of how you’ve fostered a culture of quality and excellence within your teams, as this reflects your leadership and commitment to uphold best practices.

Discuss potential strategies such as stakeholder engagement, training initiatives, and highlighting successful case studies. Emphasize your proactive approach to advocacy for Gen AI, demonstrating your understanding of its importance in the business context.

Illustrate your approach by explaining the frameworks you utilize for prioritization, such as agile methodologies or the Eisenhower matrix. Include a personal story where you successfully managed multiple projects, showcasing your organizational skills.

Explain the metrics or KPIs you find valuable, such as deployment frequency, error rates, or customer feedback. Share examples of how you have tracked success in previous projects, indicating your results-oriented mindset.

Use the STAR method to summarize your leadership experience, detailing the project goals, your role, team dynamics, challenges faced, and outcomes. This demonstrates your capability in handling diverse teams effectively.

Discuss your philosophy on mentorship and how you actively support team members’ growth. Share specific instances where your mentorship had a positive impact on an employee’s career path or confidence.

Talk about strategies such as setting clear expectations, regular check-ins, and creating an open dialogue for feedback. Illustrate your commitment to fostering a culture of trust and responsibility through real-life examples.

Highlight critical skills such as analytical thinking, attention to detail, adaptability to new technologies, and collaboration. Offering insights into how these skills have influenced your strategies will demonstrate your industry expertise.

Share resources you utilize such as industry publications, webinars, or professional networks. Emphasizing continuous learning underscores your commitment to staying knowledgeable and relevant in a fast-evolving field.