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.
This role sits within an AI-first engineering team building production-grade agentic systems powered by large language models (LLMs).
Engineers design and implement multi-agent orchestration frameworks, retrieval-augmented generation (RAG) pipelines, tool-calling integrations, and LLM inference services — all at enterprise scale on on-premise infrastructure.
Key Skills for This Role
helmjavajenkinskuberneteslangchainpostgresql
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Qualifications
Basic Qualifications:
2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)
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 (e.g. Masters, MBA, JD, MD)
2+ years of relevant work experience and a Bachelor's degree, OR 5+ years of relevant work experience.
Experience in technologies/software systems or a directly related field (minimum two years).
Experience in developing and/or implementing web-based or mobile applications (minimum two years).
Experience in system design and architecture for product components.
Experience in debugging and troubleshooting software issues.
Experience in code review and applying coding standards.
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Experience in test planning and execution for software features.
Experience in responding to support requests and deploying fixes.
Experience in using software developer tools for code creation and maintenance.
Experience developing backend services in Java (Java 17+ preferred; Java 21 a strong plus).
Familiarity with REST API design, Spring Boot, and JPA/ORM-based data access patterns.
Foundational understanding of LLM APIs — prompt construction, token limits, and response parsing.
Experience building and testing enterprise-scale web services (minimum one year).
Experience working on client-facing project or technical teams (minimum one year).
Experience in integrating feedback into design and solution fixes.
Experience in mentoring junior engineers and collaborating with cross-functional teams.
Hands-on experience building agentic AI systems using LangGraph, LangChain, LangGraph4j, or LangChain4j — specifically multi-agent graph construction, node/edge definitions, conditional routing, and state schema design.
Experience implementing the React prompting pattern (Thought → Action → Observation) in a production or near-production LLM application.
Working knowledge of Model Context Protocol (MCP) — server registration, tool schema definition (tools/list, tools/call), and client-side integration.
Experience building RAG pipelines: document chunking strategies, embedding models, vector database querying (pgvector, Pinecone, Weaviate, or equivalent), and retrieval relevance tuning.
Experience with prompt engineering — including structured output enforcement (JSON schema), chain-of-thought prompting, few-shot example design, and system prompt management.
Experience building and monitoring LLM observability — tracking token usage, latency per agent step, tool call success rates, and output quality metrics in production.
Experience with PostgreSQL including the pgvector extension for embedding storage and similarity search.
Experience deploying containerized workloads on Kubernetes or OpenShift, including Helm chart authoring, rolling deployments, and health probes.
Experience designing audit logging for AI agent decisions — capturing inputs, reasoning traces, tool calls, and outputs in a structured, queryable format.
Familiarity with Aspect-Oriented Programming (AOP) for cross-cutting concerns such as agent call logging, latency measurement, and security enforcement in Spring Boot.
Experience with CI/CD pipelines (Jenkins or equivalent) for AI/ML service deployments, including version gating and environment promotion strategies.
Information for US Applicants
Work Hours
Varies upon the needs of the department.
Travel Requirements
This position requires travel 5-10% of the time.
Mental/Physical Requirements
This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.
Visa is an EEO Employer
About Visa
Financial Services10,001+Founded 1958
Visa is a global payments technology company that connects consumers, businesses, banks, and governments in over 200 countries through its electronic payment network, VisaNet.