Lead Software Engineer, Cloud Native Platforms

Visa

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Foster City, CA
Salary: $192,300–$307,600 / yr
Employment: Full-time
Posted: 72 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $176k

This role $250k

$88k $331k

below market most similar roles pay here above market

This role pays more than 93% of similar roles. Most pay $151,000–$201,600 — the blue band above. At the midpoint, this role pays about $250k versus about $176k for comparable roles.

Based on 240 similar postings.

Employer

About Visa

Visa Inc. is the world''s largest payment network, enabling digital payments for consumers, merchants, financial institutions, and governments through its global processing network and branded card products. Industry: Payments Technology & Financial Services

Visa currently has 112 open roles on FindRole.

Listed pay typically runs $154,200–$251,100 across 108 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer, Cloud Native Platforms

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Lead Software Engineer – Cloud Native Platforms (GCP) joins the engineering team to design, build, and operate secure, scalable, and high-performance cloud-native platforms. This role involves developing mission-critical services that support high transaction volumes and demanding availability requirements within a global-scale business environment. You will build cloud-native applications on Google Cloud Platform using Kubernetes (GKE), containerization, and CI/CD pipelines while driving performance engineering for throughput optimization and latency reduction. Key responsibilities include implementing Canary and Blue-Green deployments, managing infrastructure as code via Terraform, and utilizing Java/J2EE, RESTful APIs, and microservices. You will also perform root-cause analysis, mentor engineers, and leverage agentic workflows to improve developer productivity. The work focuses on solving complex distributed systems problems to ensure reliable, low-latency processing for large-scale transaction volumes.

Skills

Google Cloud Platform (GCP) Kubernetes GKE Java J2EE Docker CI/CD Terraform Microservices RESTful APIs Distributed Systems Infrastructure as Code Canary Deployments Blue-Green Deployments JVM Tuning Observability Cloud Monitoring Cloud Logging Performance Engineering

What you'll do

Design, develop, and operate scalable, secure, and highly available cloud-native applications on Google Cloud Platform.
Build distributed systems capable of supporting high transaction volumes with strict latency and availability requirements.
Drive performance engineering initiatives including throughput optimization, latency reduction, and capacity planning.
Implement modern deployment strategies such as Canary, Blue-Green, and automated rollback mechanisms.
Translate business requirements into extensible, resilient, and maintainable technical solutions.
Lead architecture discussions, design reviews, and technical decision-making processes.
Troubleshoot complex production issues and perform root-cause analysis to drive long-term reliability.
Mentor engineers and enforce engineering best practices like secure coding and automated testing.

What we're looking for

Must have 10+ years of relevant work experience with a Bachelor’s Degree.
Must have at least 7 years of work experience with an Advanced degree (Masters, MBA, JD, MD).
Must have 4 years of work experience with a PhD.
Must have 13+ years of relevant work experience.
12+ years of software engineering experience in enterprise, fintech, payments, or highly regulated environments (preferred).
Strong hands-on experience with Google Cloud Platform (GCP), including GKE, Cloud Monitoring, Cloud Logging, cloud networking, and cloud security services (preferred).
Deep expertise in Java/J2EE, RESTful APIs, microservices, and distributed systems (preferred).
Experience with Kubernetes, Docker, CI/CD, and modern software delivery practices (preferred).

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