Staff SW Engineer - Performance Engineer

Visa•Foster City, CA

3h•Hybrid

About The Position

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. The Opportunity: We are looking for Versatile, curious, and energetic Software Engineers who embrace solving complex challenges on a global scale. As a Visa Software Engineer, you will be an integral part of a multi-functional development team inventing, designing, building, and testing software products that reach a truly global customer base. While building components of powerful payment technology, you will get to see your efforts shaping the digital future of monetary transactions.

Requirements

5+ years of relevant work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience.

Nice To Haves

6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
Deep Understanding of Performance KPIs and their tradeoffs and patterns
Performance Modeling capability based on Performance benchmark Numbers for a predefined application Non-Functional Requirement
Understanding of Microservices/CGROUP and Namespaces in Linux
Deep Understanding of Linux Memory management
Deep Understanding of IO Subsystem (IO subsystem layers, Type of IOs, Caching, Filesystems, RAID)
Understanding of Compute subsystem with in-depth knowledge of scheduling of process, thread and goroutines/LWT
Understanding of process state, context switches, system calls
Understanding of NW layers – protocols, flow control and congestion control
Some knowledge on Data Center
Knowledge of at least one language - GoLang, Python or Java. Should be able to code independently
Ability to build Cost Profile for Application based on test results [CPU, Memory, IO, and Network]
Ability to profile CPU and Memory consumptions or raw dumps. Familiarity with traces, thread dumps, debug log
Create performance test strategy and test cases
Design Chaos test case scenarios and formulate test strategy by identifying failure points
Energy and Experience: A growth mindset that is curious and passionate about technologies and enjoys challenging projects on a global scale
Challenge the Status Quo: Comfort in pushing the boundaries, ‘hacking’ beyond traditional solutions
Builder: Experience building and deploying modern services and web applications with quality and scalability
Learner: Constant drive to learn new technologies such as Angular, React, Kubernetes, Docker, etc.
Partnership: Experience collaborating with Product, Test, Dev-ops, and Middleware teams

Responsibilities

Accountable for highly scalable, low-latency payment solutions with a focus on performance & resiliency.
Lead component-level performance engineering, including code analysis and data flow.
Design and execute performance, resiliency, and load tests for critical applications.
Developing autonomous AI agents capable of planning, executing, and adapting throughout multi-step, complex performance evaluations with minimal human oversight.
Identify bottlenecks, analyze root causes, and recommend corrective actions.
Code Refactoring for Performance: Feeding problematic code snippets into LLMs to receive optimized, faster, or lower-memory-consuming versions of the code.
AI-Assisted Scripting & Optimization: Automated Test Script Generation, Code Refactoring for Performance, Database Query Optimization, Kafka pub-sub latency and throughput tuning
Collaborate with cross-functional teams to document NFR and best practices.
Monitor system performance, prepare reports, and present technical findings.
Develop tools and frameworks for profiling, observability, and process improvements.
Anomaly Detection: Implementing GenAI models to monitor real-time metrics and automatically detect anomalies, reducing the time required for troubleshooting.
Designing autonomous AI agents that can plan, execute, and adapt across multi-step, complex performance tests without constant human intervention.
Advise teams on best practices that can improve scalability, resiliency of solutions
Accountable troubleshooting production issues pertaining to performance and resiliency.