Sr. Software Engineer

Visa · Bengaluru · 2+ yrs experience · Posted 2026-05-25

Tech stack: Docker, GraphQL, Java, JavaScript, Kubernetes, Python, React, Spring Boot, TypeScript

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About the role

At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.
Responsibilities:
- Software Development Engineers are expert problem-solvers and builders who design, implement, and improve software applications and systems. In this role, engineers spend approximately 60–75% of their time coding, working hands-on with code, data, and modern tools (including AI-assisted development, cloud services, and automation frameworks) to deliver secure, scalable, and high-quality technology solutions that drive business outcomes in the fintech sector. They collaborate with cross-functional teams – product managers, designers, data scientists, QA, operations, and compliance – to translate business requirements into robust technical solutions, all while adhering to best practices, security standards, and regulatory requirements.
- All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work.
- Architect, develop, and maintain full-stack applications using Java Spring Boot, Python, React, and JavaScript
- Apply strong DSA knowledge to build high-performance backend services and efficient front-end interactions
- Leverage GenAI coding tools (Cline, Copilot, etc.) to accelerate development, reduce boilerplate, and ensure high engineering productivity
- Design and implement robust microservices, REST/GraphQL APIs, and modular front-end components
- Participate in code reviews, architectural discussions, and engineering best‑practice improvements
- Work closely with technical and non-technical stakeholders to integrate GenAI capabilities into existing systems and workflows
- Ensure code quality, scalability, observability, and system reliability across the full development lifecycle
- Contribute to performance tuning, monitoring, and long-term maintainability of mission-critical services
Qualifications:
- Master’s degree in Computer Science, Engineering, or related technical field and 2+ years of professional software engineering experience, OR
- Bachelor’s degree in a related field and 5+ years of professional software engineering experience
- Strong full‑stack development expertise with Java (Spring Boot) and Python, including experience building scalable backend services
- Front‑end development proficiency using React, JavaScript, and modern UI development practices (component-driven architecture, hooks, state management, TypeScript is a plus)
- Deep expertise in Data Structures and Algorithms, with the ability to implement optimized solutions and reason clearly about performance trade-offs
- Strong command of object-oriented design, architectural patterns, and implementation of standard design patterns (Factory, Singleton, Observer, Facade, etc.)
- Experience with multi-threading, concurrency models, asynchronous programming, and robust error-handling strategies
- Proven experience performing troubleshooting, root-cause analysis, and designing reliable, maintainable enterprise-grade systems
- Hands-on experience with Git-based workflows, CI/CD pipelines, automated testing frameworks, and secure coding best practices
- Preferred
- Proficiency with Generative AI coding assistants, such as Cline, GitHub Copilot or other AI-augmented development tools
- Foundational understanding of GenAI technologies, LLMs, embeddings, prompt engineering, and model-driven product enhancements
- Familiarity with agentic AI frameworks and emerging patterns for building autonomous or co-pilot style AI systems
- Ability to evaluate and integrate GenAI-powered capabilities into engineering workflows or product features, particularly in fintech or complex enterprise domains
- Experience collaborating with cross-functional teams (product, design, cloud engineering, SRE, data science) to deliver cohesive and innovative solutions
- Understanding of microservices, distributed systems, containerization (Docker), orchestration (Kubernetes), and API gateway patterns
- Experience with relational and NoSQL databases, query optimization, and performance tuning

Qualifications

- Master’s degree in Computer Science, Engineering, or related technical field and 2+ years of professional software engineering experience, OR
- Bachelor’s degree in a related field and 5+ years of professional software engineering experience
- Strong full‑stack development expertise with Java (Spring Boot) and Python, including experience building scalable backend services
- Front‑end development proficiency using React, JavaScript, and modern UI development practices (component-driven architecture, hooks, state management, TypeScript is a plus)
- Deep expertise in Data Structures and Algorithms, with the ability to implement optimized solutions and reason clearly about performance trade-offs
- Strong command of object-oriented design, architectural patterns, and implementation of standard design patterns (Factory, Singleton, Observer, Facade, etc.)
- Experience with multi-threading, concurrency models, asynchronous programming, and robust error-handling strategies
- Proven experience performing troubleshooting, root-cause analysis, and designing reliable, maintainable enterprise-grade systems
- Hands-on experience with Git-based workflows, CI/CD pipelines, automated testing frameworks, and secure coding best practices
- Proficiency with Generative AI coding assistants, such as Cline, GitHub Copilot or other AI-augmented development tools
- Foundational understanding of GenAI technologies, LLMs, embeddings, prompt engineering, and model-driven product enhancements
- Familiarity with agentic AI frameworks and emerging patterns for building autonomous or co-pilot style AI systems
- Ability to evaluate and integrate GenAI-powered capabilities into engineering workflows or product features, particularly in fintech or complex enterprise domains
- Experience collaborating with cross-functional teams (product, design, cloud engineering, SRE, data science) to deliver cohesive and innovative solutions
- Understanding of microservices, distributed systems, containerization (Docker), orchestration (Kubernetes), and API gateway patterns
- Experience with relational and NoSQL databases, query optimization, and performance tuning

Responsibilities

- Software Development Engineers are expert problem-solvers and builders who design, implement, and improve software applications and systems.
- In this role, engineers spend approximately 60–75% of their time coding, working hands-on with code, data, and modern tools (including AI-assisted development, cloud services, and automation frameworks) to deliver secure, scalable, and high-quality technology solutions that drive business outcomes in the fintech sector.
- They collaborate with cross-functional teams – product managers, designers, data scientists, QA, operations, and compliance – to translate business requirements into robust technical solutions, all while adhering to best practices, security standards, and regulatory requirements.
- All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work.
- Architect, develop, and maintain full-stack applications using Java Spring Boot, Python, React, and JavaScript
- Apply strong DSA knowledge to build high-performance backend services and efficient front-end interactions
- Leverage GenAI coding tools (Cline, Copilot, etc.) to accelerate development, reduce boilerplate, and ensure high engineering productivity
- Design and implement robust microservices, REST/GraphQL APIs, and modular front-end components
- Participate in code reviews, architectural discussions, and engineering best‑practice improvements
- Work closely with technical and non-technical stakeholders to integrate GenAI capabilities into existing systems and workflows
- Ensure code quality, scalability, observability, and system reliability across the full development lifecycle
- Contribute to performance tuning, monitoring, and long-term maintainability of mission-critical services

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