Level

VisaPosted 1mo ago

Staff SW Engineer- Java backend with GenAI experience

Staff SW Engineer- Java backend with GenAI experience at Visa scores 50 out of 100 on AI centrality, which makes it AI Level 2 of 4 (Uses AI) on this board. The level measures how much of the work is AI, not seniority.

IN - Bengaluru, IndialeadFull time

AI in this role

chatgptopenaiclaudecopilotllamaopenai-apiazure-openaipineconeweaviatechromacursor
prompt-engineeringragllm-integrationfine-tuning

About Us
Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.

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.

Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you.

Job Description

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.
Key Responsibilities:

  • Collaborate with stakeholders to determine requirements for product components and incorporate feedback into future designs or solutions.
  • Translate functional requirements into system designs and communicate component interactions, ensuring alignment with business needs and timelines.
  • Design and develop product components, refine code plans, and lead design reviews to ensure completeness and adherence to requirements.
  • Contribute to project estimation, considering delivery costs and escalating issues that may cause delays.
  • Lead by example in creating, implementing, and maintaining extensible, reusable code, and drive code quality through metrics and best practices.
  • Apply debugging tools to resolve moderately complex issues and identify opportunities for automation across products.
  • Lead code reviews, ensuring adherence to coding standards and providing feedback to team members.
  • Create complex test plans, identify test gaps, and proactively address defects to minimize customer impact.
  • Leverage data analysis and monitoring standards to identify patterns and defects in all environments.
  • Respond to incidents during on-call rotations, troubleshoot complex issues, and assist in incident response and resolution.
  • Build, enhance, and identify new developer tools to support programs and applications.
  • Proactively seek new knowledge and adapt to trends and technical solutions to improve product performance and recommend resources to other engineers.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Qualifications

Education & Experience:

7.5+ years of relevant software engineering experience

Bachelor's or Master's degree in Computer Science, Software Engineering, Distributed Systems, or related field

Core Technical Skills:

Java & Distributed Systems Expertise:

Extensive technical experience with JAVA, Spring, Hibernate

Advanced Java development including concurrency, multithreading, and performance optimization

Deep understanding of distributed system architectures (microservices, event-driven, service mesh)

Experience with distributed consensus algorithms (Raft, Paxos) and coordination services (Zookeeper, etcd)

Proficiency in distributed data management patterns (CQRS, Event Sourcing, Saga patterns)

Strong knowledge of distributed caching (Redis, Hazelcast, Memcached)

Experience with message queues and streaming platforms (Kafka, RabbitMQ, Pulsar)

Understanding of CAP theorem, eventual consistency, and distributed transaction management

Experience building highly available, fault-tolerant systems with disaster recovery capabilities

Knowledge of service discovery, load balancing, and circuit breaker patterns

Proficiency in code development using Eclipse/MyEclipse, JetBrains IntelliJ or any major Java IDE

Strong experience with GIT/Stash, Maven, and Jenkins

API & Integration:

Extensive experience in API Development using SOAP or REST, JSON and XML

Deep knowledge of API standards including OAuth, SAML

Experience with GraphQL, gRPC, and modern API gateway patterns

Understanding of API versioning, rate limiting, and distributed API management

Experience building async/reactive APIs using Spring WebFlux or similar frameworks

Data & Infrastructure:

Experience with SQL datastores (DB2/MySQL) and Unix/Linux platforms

Understanding of database sharding, replication, and distributed database systems

Experience with distributed file systems (HDFS, S3, or similar)

Knowledge of data consistency patterns across distributed datastores

Proven experience with tools development, automation (CI/CD, Auto Deployment, System Availability), logging and monitoring

Experience with distributed tracing (Jaeger, Zipkin, OpenTelemetry)

Working knowledge of streaming platforms like Kafka for real-time data processing

AI-First Engineering Skills:

Hands-on experience with LLM integration and serving at scale (OpenAI API, Azure OpenAI, Claude, Llama, etc.)

Proficiency in AI-assisted development tools (GitHub Copilot, Cursor, Cline, or similar)

Experience building intelligent APIs with AI/ML inference endpoints in distributed environments

Understanding of vector databases (Pinecone, Weaviate, ChromaDB) for RAG applications

Knowledge of prompt engineering and AI model fine-tuning

Distributed Systems Design:

Experience designing scalable microservices architectures handling millions of transactions

Knowledge of distributed system monitoring and observability (Prometheus, Grafana, ELK stack)

Understanding of container orchestration in distributed environments

Experience with chaos engineering and resilience testing

Proficiency in distributed debugging and troubleshooting techniques

Professional Capabilities

Ability to write clean, coherent code following established coding guidelines

Strong interpersonal and effective communication skills (both written and verbal)

Highly driven, resourceful, and results-oriented

Experience leveraging AI tools to accelerate development velocity and code quality

Ability to design and communicate distributed system architectures effectively

Visa is an EEO Employer

Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringRagLlm IntegrationFine TuningChatGPTOpenAIClaudeCopilot

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. How have you integrated a large language model into a production application?
  4. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  5. Walk me through how you've used ChatGPT in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Prompt Engineering, Rag, Llm Integration, Fine Tuning, and ChatGPT. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Put the AI tool in a bullet point about what you did, not just in a skills list — this role treats it as a required part of the job.

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