Software Engineer II; AI Platform Engineer

Staff Software Engineer II (AI Platform Engineer)

Visa

Join us to make an impact as an AI platform engineer with Visa, a world leader in payments and technology.

Visa’s Technology Organization is a community of problem solvers and innovators reshaping the future of commerce. We operate the world’s most sophisticated processing networks capable of handling more than 65k secure transactions a second across 80M merchants, 15k Financial Institutions, and billions of everyday people. While working with us you’ll get to work on complex distributed systems and solve massive scale problems centered on new payment flows, business and data solutions, cyber security, and B2C platforms.

Visa is building a next‑generation Agentic AI services that brings intelligent, autonomous agents into large‑scale distributed applications across our global ecosystem.

We’re seeking a Sr. Consultant Software Engineer who will architect, design, and build scalable backend systems that integrate AI agents into Visa’s enterprise infrastructure. You will work with other Senior Engineers and technical leaders to define the architecture, scaling strategy, and engineering standards for Visa’s AI‑driven products. This is a role for a hands‑on technical leader — a go‑getter, builder, and problem solver with deep experience in Java microservices, GenAI integration, and distributed system design, and a true‑north, entrepreneurial mindset focused on speed, quality, and innovation.

• Architecture & Design:
  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.
• AI & GenAI Integration:
  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 Lang Chain, Lang Graph, or Autogen.
• Scalability & Reliability:
  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.
• Leadership & Execution:
  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.
• Innovation & Strategy:
  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.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

This role does not offer relocation or immigration support now or in the future.

• 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.

• 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…