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Visa · 14 hours ago

Staff Software Engineer II (AI Platform Engineer)

Bellevue, WA

Full-time

Hybrid

Lead/Staff

$152K/yr - $244K/yr

8+ years exp

Visa is a world leader in payments and technology, and they are seeking a Staff Software Engineer II to architect, design, and build scalable backend systems that integrate AI agents into Visa’s enterprise infrastructure. The role requires collaboration with senior engineers and technical leaders to define architecture, scaling strategy, and engineering standards for AI-driven products.

BankingFinanceFinancial ServicesInformation TechnologyMobile PaymentsPayments

Comp. & Benefits

No H1B

Responsibilities

Architect and evolve the Agentic AI Platform to support multi-agent orchestration, retrieval-augmented generation (RAG), and integration with existing Visa microservices

Design scalable, secure backend systems using Java (Spring Boot) and Python (FastAPI/Flask)

Develop RESTful and gRPC APIs that connect backend services, AI agents, and React front-end applications

Integrate Large Language Models (LLMs) such as GPT, Claude, Mistral, and Gemini into backend systems

Build and optimize RAG pipelines using vector databases (Pinecone, Weaviate, FAISS)

Develop orchestration and agentic workflows using LangChain, LangGraph, or Autogen

Lead the design and implementation of distributed, fault-tolerant systems that scale horizontally

Implement auto-scaling, monitoring, and observability using Kubernetes, Docker, and Prometheus/Grafana

Drive best practices for latency reduction, cost optimization, and service reliability

Partner with other senior engineers, ML engineers, and product leads to define and deliver the platform roadmap

Mentor developers, set coding standards, and lead design reviews

Deliver results with urgency — balancing innovation with enterprise rigor

Explore new frameworks, architectures, and deployment models to push the boundaries of Agentic AI in production

Drive continuous improvement, automation, and open-source adoption across the engineering organization

Qualification

Java microservicesAI integrationDistributed system designBackend developmentPython FastAPIPython FlaskREST/gRPC APIsVector databasesCloud platformsContainerizationLeadershipProblem solvingCollaborationCommunication

Required

8 or more years of relevant work experience with a Bachelor's Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11 or more years of relevant work experience

Preferred

9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD

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

2 or more years of backend experience with Python (FastAPI, Flask, or similar frameworks)

Production-level experience in building and deploying AI Agentic solutions, including orchestration of LLM-based agents, integration with enterprise microservices, and troubleshooting live production environments

Hands-on experience implementing LLM, GenAI, and RAG systems using frameworks such as LangChain, LangGraph, or Autogen

Experience building and integrating Model Context Protocol (MCP) frameworks for tool and API interoperability

Strong understanding of AI orchestration and LLM integration patterns in distributed environments

Proven experience building and scaling distributed microservice architectures

Proficiency in REST/gRPC API design, event-driven architectures, and message queues (Kafka, RabbitMQ)

Experience with vector databases (Pinecone, Weaviate, FAISS) and retrieval-augmented generation (RAG) pipelines

Hands-on expertise with cloud platforms (AWS, GCP, Azure)

Familiarity with SQL and NoSQL databases (MySQL, DynamoDB, MongoDB)

Experience with containerization and CI/CD pipelines (Docker, Kubernetes, ArgoCD, Jenkins, GitHub Actions)

Excellent debugging, performance optimization, and system design skills at scale