Director- Engineering (14 - 16 Years of Experience in Java, Angular/react, Genai, Microservices)

Visa Visa · Fintech · Bengaluru, India, IN

Director of Engineering leading a team to build, modernize, and support Visa's revenue-related enterprise applications. The role involves defining technical direction, championing AI-driven engineering practices, owning architectural strategy, and guiding the delivery of secure, scalable systems. Key responsibilities include leading the design and delivery of Generative AI and ML-based applications, fostering innovation, and developing engineering talent with a focus on AI and modern practices.

What you'd actually do

  1. Define and own the technical and architectural strategy for Visa’s revenue‑related enterprise applications, ensuring scalability, performance, security, and resiliency.
  2. Drive proofs of concept and evaluate emerging/open‑source technologies, making informed recommendations and platform decisions that align with enterprise architecture standards.
  3. Provide deep technical leadership in application design, including reviewing and guiding functional designs, system architectures, API patterns, and integration strategies.
  4. Guide teams in designing robust data models and repositories for both transactional and analytical workloads, and review data‑related designs for quality and scalability.
  5. Ensure delivery of high‑quality, production‑ready software through strong engineering best practices, CI/CD pipelines, test automation, observability, and operational excellence.

Skills

Required

  • Java
  • Angular/React
  • GenAI
  • Microservices
  • application design
  • system architectures
  • API patterns
  • integration strategies
  • data models
  • CI/CD pipelines
  • test automation
  • observability
  • operational excellence
  • engineering talent development
  • cloud
  • modern engineering practices

What the JD emphasized

  • lead the end‑to‑end design and delivery of Generative AI and ML‑based applications

Other signals

  • leading AI-driven engineering practices
  • designing intelligent solutions for complex business needs
  • experiment, innovate, and apply AI across the engineering lifecycle
  • end-to-end design and delivery of Generative AI and ML-based applications