Software Engineer - Sr. Consultant level

About Us

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

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.

Key Responsibilities

• 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).

• 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).

• 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.

• 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.

Qualifications

• Basic Qualifications
  8+ 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+ years of relevant work experience.

• Preferred Qualifications
  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.

• 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.

• Leadership Attributes: Go-Getter, Builder, Hustler, Entrepreneurial, True North, Lead by Example, Execute with Excellence.

Tech Stack Snapshot

• Languages: Java (Spring Boot), Python (FastAPI, Flask), TypeScript
• AI Frameworks: LangChain, LangGraph, Autogen, LlamaIndex
• LLMs: GPT, Claude, Mistral, Gemini
• Data: MySQL, Hazelcast, Pinecone, FAISS
• Infra: Docker, Kubernetes, ArgoCD, AWS/GCP
• Frontend Integration: React, GraphQL, REST/gRPC APIs