Sr. Staff SW Engineer at Visa

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

05 Jul, 26

Salary

0.0

Posted On

06 Apr, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Software Engineering, Distributed Systems, Generative AI, LLMs, RAG, Java, Python, C#, C++, API Development, System Architecture, Cloud-native, Containerization, CI/CD, Observability, Performance Optimization

Industry

IT Services and IT Consulting

Description

Company Description 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 The Opportunity We are looking for a dedicated, curious, and highly skilled Software Engineer to help architect and build intelligent, AI-native platforms that operate at global scale. In this role, you will take ownership of critical technical components across intelligent application layers - from backend services and orchestration engines to front-end interaction models. You will build production-grade systems that integrate large language models, retrieval frameworks, enterprise APIs, and workflow automation capabilities. The Work Itself Design and implement scalable AI-enabled services integrating LLMs, RAG pipelines, semantic search, and enterprise data systems Build orchestration layers supporting multi-step workflows, tool invocation, and context-aware task execution Develop secure, performant APIs that connect intelligent systems with internal platforms and data sources Contribute to full-stack development, including intuitive human–AI interaction experiences Ensure production readiness through monitoring, evaluation, observability, and performance optimization Improve reliability, latency, and scalability of AI-powered services Provide technical guidance to engineers within the team on complex system design and implementation challenges Contribute to reusable components and engineering best practices for AI-native development Essential Functions Partner with product and engineering teams to translate AI-driven requirements into robust technical designs Independently lead the technical implementation of high-complexity features or subsystems Make critical architectural decisions within defined product or platform boundaries Identify technical risks early and propose scalable, maintainable solutions Contribute to documentation and knowledge sharing for AI-enabled system patterns Participate in sprint planning, estimation, and retrospectives. Apply secure coding practices and comply with regulatory and data protection standards. The Skills You Bring Advanced Systems Engineering: Strong experience designing distributed systems, APIs, and scalable backend services. AI Application Experience: Hands-on experience building or integrating generative AI capabilities such as LLMs, RAG architectures, embeddings, semantic retrieval, or workflow automation. Full Stack Proficiency: Experience developing backend systems (e.g., Java, Python, C#, C++) and collaborating on or contributing to modern front-end frameworks. Execution Depth: Ability to independently deliver complex, cross-service features with attention to performance, reliability, and maintainability. Enterprise Integration: Experience integrating applications with internal APIs, data platforms, and secure enterprise environments. Production Mindset: Experience operationalizing AI-enabled services, including logging, evaluation, monitoring, and scalability considerations. Collaborative Engineering: Ability to work effectively across Product, Data Science, DevOps, and Agile teams. We value engineers who combine deep technical expertise with curiosity about emerging AI technologies and who thrive in building complex, high-impact systems. Qualifications Basic Qualifications •Master's degree in Math, Science, Engineering, or Computer Science, Information Systems or related field AND minimum six (6) years of experience in a directly related field. OR •Bachelor's degree in Math, Science, Engineering, or Computer Science, Information Systems or related field AND minimum eight (8) years of experience in a directly related field. OR •Minimum eleven (11) years of directly related experience. Preferred Qualifications •Experience developing both front-end and back-end components for enterprise platforms. •Experience building or integrating generative AI applications, including large language models (LLMs), retrieval-augmented generation (RAG), embeddings, or semantic search systems. •Experience building or integrating generative AI applications, including large language models (LLMs), retrieval-augmented generation (RAG), embeddings, or semantic search systems. •Experience working with structured and unstructured data sources, vector databases, and knowledge indexing systems. •Experience deploying services in cloud-native environments using containerization and CI/CD pipelines. •Exposure to payments, fintech, or high-volume transactional systems. •Experience implementing observability, evaluation, and performance monitoring for production systems Strong understanding of distributed systems, data structures, and system integration patterns. Additional Information 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. Job Family Group: Engineering and Technology

Responsibilities

Design and implement scalable AI-enabled services integrating LLMs, RAG pipelines, and enterprise data systems. Provide technical guidance to engineering teams while ensuring production readiness, reliability, and performance optimization.