Description
Software Development Engineers at Visa are expert problem-solvers and builders who design, implement, and improve software applications and systems. In this role, you will spend approximately 60–75% of your time coding, working hands-on with code, data, and modern tools to deliver secure, scalable, and high-quality technology solutions that drive business outcomes in the fintech sector.
You will collaborate with cross-functional teams to translate business requirements into robust technical solutions, all while adhering to best practices, security standards, and regulatory requirements. This role sits within an AI-first engineering team building production-grade agentic systems powered by large language models (LLMs).
Key Responsibilities:
- Collaborate with stakeholders to interpret requirements for project components and incorporate feedback into future designs or solution fixes.
- Translate business requirements by verifying assumptions and escalating potential design issues to appropriate stakeholders.
- Participate in system design and architecture, refining code plans and contributing to design documentation.
- Contribute to project estimation and escalate issues that may cause delays.
- Develop, implement, and maintain code for products, services, or components, applying coding patterns, guidelines, and best practices.
- Apply debugging tools to verify assumptions and proactively flag issues before they occur.
- Participate in code reviews to ensure coding standards are followed and address routine pull requests.
- Create test plans and configure testing procedures to identify and resolve defects for multiple features.
- Respond to support requests during on-call rotations, troubleshooting issues and deploying fixes under guidance.
- Leverage and build knowledge of software developer tools to create, debug, and maintain code for components.
- Remain current in skills by investing time in training resources to improve product availability, reliability, efficiency, observability, and performance.
AI & Agentic Systems:
- Design, implement, and tune multi-agent LLM workflows using agent orchestration frameworks.
- Build and maintain ReAct agent loops , iterative Reason→Act→Observe cycles.
- Implement Supervisor/Orchestrator agent patterns where a Lead Agent dynamically plans, spawns, and coordinates Specialist Sub-Agents.
- Develop MCP tool servers that expose enterprise data sources as callable tools for AI agents.
- Implement and refine RAG pipelines: document ingestion and chunking, embedding generation, vector storage, and semantic similarity retrieval.
- Integrate with enterprise LLM inference gateways via REST APIs.
- Design and implement agent memory architectures , both short-term per-agent isolated context stores and long-term shared knowledge repositories.
- Build confidence scoring and uncertainty quantification mechanisms for AI-generated outputs.
- Implement agent feedback loops , capturing human reviewer decisions and feeding structured corrections back into prompt templates and knowledge repositories.
Qualifications:
- Basic Qualifications: 2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree.
- Preferred Qualifications: 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree.