Director, Software Engineering

Visa

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Foster City, CA
Salary
$219,100–$350,800 / yr
Employment
Full-time
Posted
10 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $235k
This role $285k
$148k most similar roles pay here $373k

This role pays more than 82% of similar roles. Most pay $208,800–$262,112 — the shaded band above. At the midpoint, this role pays about $285k versus about $235k for comparable roles.

Based on 240 similar postings.

Employer

About Visa

Visa Inc. is the world''s largest payment network, enabling digital payments for consumers, merchants, financial institutions, and governments through its global processing network and branded card products. Industry: Payments Technology & Financial Services

Visa currently has 88 open roles on FindRole.

Listed pay typically runs $149,200–$238,700 across 84 roles with salary data.

Most-posted roles

View all roles at Visa

At a glance

TL;DR · Director, Software Engineering

Director, Software Engineering joins the Acceptance Solutions Product Development team to lead engineers building secure, high-performing distributed systems for payment acceptance. This role involves managing the design, implementation, and deployment of robust payment products while remaining hands-on with architecture, code reviews, and technical troubleshooting. The candidate will develop search, indexing, analytics, and data-processing capabilities to support high-volume transaction use cases. Key responsibilities include defining technical strategy for payment processing platforms, implementing event-driven data flows, and applying AI/ML and Generative AI to improve engineering productivity. The required technology stack includes Java, Containers, Kafka, relational databases, Docker, and Kubernetes. The role addresses the complexity of digital commerce by building an open, modular API platform that ensures Visa-grade resilience and security for global payment acceptance across various channels.

What you'll do

  • Lead the design, implementation, and deployment of secure, high-performing distributed payment acceptance products.
  • Perform hands-on technical tasks including architecture reviews, code reviews, troubleshooting, and production readiness decisions.
  • Define and execute technical strategies for payment processing platforms aligned with product vision and business goals.
  • Apply AI/ML and Generative AI technologies to improve engineering productivity and business outcomes.
  • Establish best practices for software development, testing, deployment, observability, and incident response.
  • Partner with security, risk, and compliance teams to ensure products meet regulatory standards and safety requirements.
  • Mentor and coach engineers through technical deep dives, design reviews, and career development discussions.
  • Communicate technical strategies, risks, and delivery progress clearly to executive leadership and cross-functional partners.

What we're looking for

  • A Bachelor's degree and 10 years of relevant experience, or 13 years of relevant experience without a degree.
  • Demonstrated experience leading software engineering teams, including people management, coaching, and delivery accountability (preferred).
  • Experience designing and operating mission-critical distributed systems with high availability, scalability, and security (preferred).
  • Proficiency in modern software engineering practices, API design, system design, and cloud-native technologies like Kubernetes and Docker (preferred).
  • Experience with event-driven architecture, Kafka, and high-throughput transaction or data processing systems (preferred).
  • Experience delivering secure software platforms including authentication, encryption, and compliance standards like PCI-DSS (preferred).
  • Hands-on experience with Java/J2EE, Spring Boot, REST, and CI/CD pipelines (preferred).
  • Experience implementing AI/ML or Generative AI capabilities in production environments or engineering workflows (preferred).

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