Software Engineer - Sr. Consultant Level (10+ years, Big Data, Architecture, Design)

Overview

Staff Software Engineer role within Visa's Payment Fraud Disruption engineering team, shaping the technical strategy and architecture of next-generation Data Engineering and Generative AI platforms that support fraud detection, investigation, risk intelligence and operational excellence.

What you'll do

• 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.

What you'll need

• 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.

Nice to have

• 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 and 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.

Details

• Location: Bengaluru, India.
• Work mode: at least 3 days in office per week; specific expectations to be confirmed by the Hiring Manager.