Sr. Software Development Engineer (Controlplane)

Zscaler•San Jose, CA

13d•Hybrid

About The Position

About Zscaler Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise , we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Here, impact in your role matters more than title and trust is built on results. We say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. We believe in transparency and value constructive, honest debate —we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession , collaboration, ownership, and accountability. We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges, and want to be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity. Role We are looking for a Sr. Software Development Engineer (Controlplane) to join our team. This is a hybrid (in office 3 days a week in San Jose, CA) role, reporting to the Manager, Software Engineering in the Zero Trust Exchange department. In this role, you will lead the design and development of highly scalable, resilient, and secure control plane platform services that power the Zero Trust Exchange. You will drive architecture, influence technical strategy across teams, and deliver platform capabilities that improve reliability, operability, and developer velocity. The ideal candidate pairs deep distributed systems expertise with strong cross-functional leadership and a pragmatic, execution-focused mindset.

Requirements

Demonstrated curiosity and active exploration of AI tools, with a proven history of integrating new technologies to enhance daily workflows and augment problem-solving
3+ years of software engineering experience, including significant experience designing and building large-scale distributed systems and backend platform services
Deep expertise in system design, microservices architecture, API design, data modeling, and operating highly available, fault-tolerant services in production environments
Strong proficiency in one or more modern programming languages such as Java, Go, or Python, with a track record of delivering production-grade software
Experience leading complex technical initiatives across multiple teams, driving architectural decisions, and influencing engineering direction beyond immediate team boundaries
Strong understanding of cloud-native technologies, observability, reliability engineering, and secure software development practices

Nice To Haves

Experience applying AI-forward engineering practices, such as developer copilots, intelligent automation, AI-assisted incident analysis, or ML/LLM-powered platform capabilities, to improve engineering productivity or product outcomes
Experience building control plane, policy, identity, security, or other mission-critical platform systems in a SaaS or cybersecurity environment
Experience mentoring senior engineers and serving as a recognized technical leader for architecture, operational excellence, and engineering standards across an organization

Responsibilities

Lead the architecture, design, and delivery of large-scale control plane and platform services with a strong focus on scalability, availability, security, and operational excellence
Drive complex cross-team technical initiatives, align stakeholders on architecture and execution plans, and ensure high-quality delivery against business and engineering priorities
Identify and resolve system bottlenecks, reliability risks, and architectural gaps across distributed systems, improving performance, observability, and long-term maintainability
Set a high technical bar through design reviews, code reviews, engineering best practices, and hands-on mentorship of senior engineers across the organization
Evaluate and apply emerging technologies, including AI-assisted engineering workflows where appropriate, to improve developer productivity, system intelligence, and product delivery outcomes