Software Engineer - Sr. Consultant Level

Job Summary

The Opportunity: We are seeking an accomplished Staff Software Engineer to help shape the technical strategy and architecture of next-generation Data Engineering and Generative AI platforms within Visa's Payment Fraud Disruption engineering team.

This role combines deep hands-on engineering with technical leadership. You will influence architecture, guide engineering practices, mentor engineers, and lead the delivery of scalable data and AI platforms supporting fraud detection, investigation, risk intelligence, and operational excellence.

The ideal candidate brings strong expertise in distributed systems, data platforms, cloud-native architectures, and Generative AI, along with a track record of leading complex technical initiatives.

Responsibilities

• Lead the architecture, design, and development of scalable data platforms, APIs, and distributed services.
• Design real-time and batch processing solutions supporting fraud intelligence, analytics, and machine learning workloads.
• Drive production adoption of Generative AI, RAG, intelligent copilots, and agentic workflows.
• Partner with Product, Data Science, Platform Engineering, and Security teams to define technical strategy and execution plans.
• Improve scalability, reliability, security, observability, and operational excellence across critical platforms.
• Mentor engineers, establish reusable patterns and engineering standards, and influence technical direction across teams.

On-site requirement: Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.

Qualifications Basic Qualifications

• Bachelor's degree in computer science, Engineering, Data Science, or a related technical field.
• 8+ years of software engineering experience building enterprise-scale applications, platforms, or data-intensive systems.
• Strong programming expertise in Java and/or Python.
• Experience designing and building distributed systems, microservices, APIs, and large-scale data platforms.
• Strong understanding of system design, data structures, algorithms, scalability, and performance optimization.
• Demonstrated ability to lead complex technical initiatives, communicate architecture decisions, and influence engineering outcomes.

Preferred Qualifications Data Engineering

• Deep experience with technologies such as Apache Kafka, Apache Flink, Apache Spark, Hadoop/Hive, ClickHouse, PostgreSQL, or MySQL.
• Experience designing scalable data pipelines, streaming architectures, analytics platforms, and data quality controls.

Generative AI

• Experience building and operating production-grade applications using Large Language Models (LLMs).
• Hands-on experience with RAG, vector databases, prompt engineering, AI agents, tool calling, and orchestration patterns.
• Experience with LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.

Cloud Platform Engineering

• Experience designing cloud-native solutions on AWS, Azure, or Google Cloud Platform.
• Strong experience with Docker, Kubernetes, CI/CD pipelines, and infrastructure automation.
• Strong understanding of observability, monitoring, reliability engineering, and production operations.