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VISA Off Campus Drive 2026 – SW Engineer
VISA
Description
SW Engineer Off-Campus Drive VISA is scheduled to hire Freshers (B.E/B.Tech/B.Sc/M.E/M.Tech/M.Sc/MBA) for SW Engineer roles. Candidates looking for jobs in Bangalore can utilise this opportunity. Interested and eligible candidates can apply online as soon as possible.
The role involves building Agentic Solutions using world’s most advanced LLM models from Anthropic, OpenAI and others. Build Deep Learning solutions using AI/ML Platforms for real time transactions at a scale of 100K+ TPS and for peta bytes of Data. Design code and systems that touch 40% of the world population while influencing Visa’s internal standards for scalability, security, and reusability. Collaborate multi-functionally to create design artifacts and develop best-in-class software solutions for Visa’s commercial products and services. Actively contributes to product reliability improvements, valuable service technology, and new operations flows in diverse agile squads. Opportunities to make a difference on a global or local scale through mentorship and continued learning and experiments.
Eligibility Criteria
Bachelor’s Degree in Computer Science, or related technology/engineering discipline. Preferred Qualifications: 1 – 2 years of work experience with a Bachelor’s degree or Advanced Degree (e.g. Masters, MBA, JD, MD) in Computer Science, or related technology/engineering discipline. Exposure in developing agentic solutions using Cline, Claude, GitHub Copilot, Power Automate etc. Experience in Software Development with Agile and full SDLC using programming languages such as (e.g., Java, GO, Python, Scala, Java scripts, .Net) etc. Development experience in building and using Microservices with HTTP, REST, JSON. Experience with a Relational database and/or NoSQL database. Proficient in GIT/Stash, Maven and Jenkins. Exposure in streaming platform like Kafka. Exposure with tools development, automation (CI/CD, Auto Deployment, System Availability, etc.), logging and monitoring. Knowledge of large scale data analytics and statistical modelling.
