Senior Software Engineer

Visa Visa · Fintech · Bengaluru, India, IN

Visa is seeking a Sr. Software Engineer (AI Cybersecurity) to design, develop, and deliver secure, scalable, and high-quality software solutions. This role focuses on building intelligent cybersecurity systems leveraging AI, Machine Learning, and Generative AI technologies to enhance automation, detection, and response capabilities. The candidate will be a hands-on engineer coding backend services and integrating AI-driven components using modern development tools, cloud platforms, and automation frameworks.

What you'd actually do

  1. Design, develop, and maintain secure and scalable software applications.
  2. Build backend services and AI-driven components using Java and Python.
  3. Integrate Machine Learning and Generative AI capabilities into applications.
  4. Translate business and cybersecurity requirements into technical solutions.
  5. Contribute to system design, architecture, and technical decision-making.

Skills

Required

  • Java
  • Python
  • AI/ML fundamentals
  • Generative AI tools and frameworks
  • Software design and system architecture
  • Secure coding practices
  • Problem-solving and analytical thinking
  • Collaboration and communication

Nice to have

  • Knowledge of Data Science and Machine Learning concepts.
  • Experience building web-based or backend systems.
  • Strong understanding of debugging, troubleshooting, and testing practices.
  • Familiarity with Generative AI tools and coding co-pilots.
  • Understanding of GenAI frameworks and technologies (LLMs, prompt engineering, RAG, APIs).
  • Experience building scalable backend systems using Java and Python.
  • Exposure to cybersecurity platforms or secure software development practices.
  • Experience with cloud platforms and distributed systems.
  • Ability to work effectively in cross-functional teams.

What the JD emphasized

  • AI Cybersecurity
  • AI, Machine Learning, and Generative AI technologies
  • AI-driven components
  • AI/ML techniques in production environments
  • Generative AI tools and coding co-pilots
  • GenAI frameworks and technologies (LLMs, prompt engineering, RAG, APIs)

Other signals

  • AI-driven components
  • Machine Learning and Generative AI capabilities
  • AI/ML techniques in production environments