Job Overview

Visa is hiring a Staff Software Engineer for a Java backend engineering role in Bengaluru. This is a senior software engineering opportunity for professionals with strong experience in Java, distributed systems, backend development, APIs, data infrastructure, automation, and Generative AI. The role combines hands-on software development with technical leadership, architecture, code quality, reliability engineering, and collaboration across product and engineering teams.

The position focuses on building secure, scalable, reusable, and highly available technology solutions for a large-scale payments environment. The successful candidate will work extensively with modern Java technologies and distributed system patterns while also applying AI-assisted development and LLM capabilities to improve engineering productivity and product capabilities.

Key Responsibilities

• Translate business and functional requirements into clear technical designs and scalable software components.
• Design and develop backend services using Java and related enterprise technologies.
• Contribute to distributed systems using microservices, event-driven architectures, and service-oriented patterns.
• Lead design reviews and provide technical direction for complex software components.
• Build reusable and maintainable code while promoting engineering standards and measurable code quality.
• Conduct code reviews and provide constructive technical guidance to other engineers.
• Develop detailed test strategies, identify coverage gaps, and address defects before they affect customers.
• Investigate production issues using debugging, monitoring, logging, and data analysis techniques.
• Participate in on-call activities and help resolve incidents affecting production systems.
• Identify opportunities for automation, developer tooling, deployment improvements, and operational efficiency.
• Work with cross-functional teams including product, design, data science, quality assurance, operations, and compliance.
• Evaluate emerging technologies and recommend engineering approaches that improve system performance, reliability, and development velocity.
• Apply Generative AI and AI-assisted development tools where appropriate to improve software delivery and engineering quality.

Required Skills

Strong Java backend engineering experience is central to this position. Candidates should have advanced knowledge of Java development, including concurrency, multithreading, performance optimization, Spring, and Hibernate.

The role requires deep knowledge of distributed systems, including microservices, event-driven architectures, service mesh concepts, distributed consensus, eventual consistency, distributed transactions, service discovery, load balancing, and resilience patterns. Experience with patterns such as CQRS, Event Sourcing, and Saga is important for designing complex distributed applications.

Candidates should also understand distributed caching, messaging, streaming, database replication and sharding, high availability, fault tolerance, disaster recovery, and distributed debugging.

Strong API engineering experience is required, including REST or SOAP, JSON, XML, OAuth, and SAML. Knowledge of GraphQL, gRPC, API gateways, API versioning, rate limiting, and reactive API development is also relevant.

Experience with Git or Stash, Maven, Jenkins, Java IDEs such as IntelliJ, Eclipse, or MyEclipse, and modern CI/CD practices is expected.

Preferred Skills

Experience with AI-first software engineering is highly relevant. Candidates with practical experience integrating LLMs at scale, building AI-enabled APIs, using AI-assisted coding tools, developing RAG applications, applying prompt engineering, or working with model fine-tuning can bring additional value.

Knowledge of vector databases such as Pinecone, Weaviate, or ChromaDB is useful for AI and RAG workloads. Familiarity with OpenAI API, Azure OpenAI, Claude, Llama, GitHub Copilot, Cursor, Cline, or similar tools is also relevant.

Experience with observability platforms, chaos engineering, resilience testing, distributed tracing, container orchestration, and production-scale troubleshooting will further strengthen an application.

Education

A Bachelor's or Master's degree in Computer Science, Software Engineering, Distributed Systems, or a related field is required according to the job description.

Experience

The position requires 7.5 or more years of relevant software engineering experience. The job description does not specify a maximum experience limit. Candidates should be able to demonstrate substantial hands-on experience in backend engineering, Java, distributed systems, scalable architectures, APIs, data infrastructure, and production software development.

Required Technologies

Core technologies and platforms mentioned for this role include Java, Spring, Hibernate, microservices, distributed systems, event-driven architecture, service mesh, Raft, Paxos, ZooKeeper, etcd, Redis, Hazelcast, Memcached, Kafka, RabbitMQ, Pulsar, SOAP, REST, JSON, XML, OAuth, SAML, GraphQL, gRPC, Spring WebFlux, DB2, MySQL, Unix, Linux, HDFS, S3, Git, Stash, Maven, Jenkins, CI/CD, Jaeger, Zipkin, OpenTelemetry, Prometheus, Grafana, ELK, Kubernetes, OpenAI API, Azure OpenAI, Claude, Llama, Pinecone, Weaviate, ChromaDB, GitHub Copilot, Cursor, and Cline.

Soft Skills

The role requires strong written and verbal communication, effective collaboration, technical leadership, and the ability to explain distributed system architecture clearly. Candidates should be resourceful, results-oriented, proactive, and comfortable working with cross-functional stakeholders.

A strong engineering mindset is important, including the ability to learn emerging technologies, make sound technical decisions, mentor other engineers, and balance software quality with business requirements.

Benefits of Working in this Role

This role offers the opportunity to work on large-scale payment technology and solve complex backend engineering problems involving distributed systems, cloud technologies, automation, observability, and AI. The combination of Staff-level technical responsibilities and AI-focused engineering provides exposure to modern software development practices and advanced system architecture.

Work Mode

This is a hybrid position. The number of days expected in the office will be confirmed by the hiring manager.

Location

The position is based in Bengaluru, Karnataka, India. Candidates seeking Java backend jobs, distributed systems jobs, AI-enabled software engineering roles, or senior Software Jobs in Bengaluru may find this opportunity relevant.

Who Should Apply

This opportunity is best suited to experienced software engineers who have strong Java backend expertise and a proven record of designing and operating scalable distributed systems. Candidates should be comfortable working with complex architectures, production troubleshooting, API development, messaging systems, databases, automation, and observability.

Professionals with hands-on Generative AI, LLM integration, RAG, or AI-assisted development experience are particularly aligned with the role. Applicants should be able to demonstrate real engineering outcomes rather than only theoretical knowledge.

Career Growth

A Staff Software Engineer role can provide opportunities to expand technical leadership, architecture ownership, mentoring, and influence across engineering teams. Working across distributed systems, AI engineering, backend platforms, reliability, and developer tooling can also broaden expertise in modern enterprise software development.

Application Advice

Tailor your resume to emphasize measurable achievements in Java backend engineering and distributed systems. Highlight complex systems you designed or improved, production-scale services you developed, performance improvements, reliability initiatives, API platforms, messaging systems, and automation work.

Clearly mention hands-on experience with Spring, Hibernate, Kafka, databases, CI/CD, observability, and distributed architecture where applicable. If you have worked with LLMs, RAG, vector databases, AI APIs, or AI-assisted development tools, describe the actual engineering use cases and outcomes.

Avoid adding technologies you have not genuinely used. Focus on architecture decisions, technical ownership, mentoring, incident resolution, and the business or customer impact of your work.