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Zscaler is an AI-forward enterprise security company building cloud-native Zero Trust Exchange platform that protects customers from cyberattacks and data loss by securely connecting users, devices, and applications. The company leverages the world's largest security data lake to power its innovations.
You will join as a hands-on Staff Software Engineer in a hybrid role based in Singapore, reporting to the Director of Software Engineering. You will lead the design and delivery of major product capabilities focused on enabling organizations to adopt AI applications and agents safely and at scale. This is a high-impact individual contributor role with significant technical leadership responsibilities.
Key responsibilities include: leading the design and delivery of major product capabilities from problem definition through implementation, rollout, and production operation; designing secure, reliable, and scalable systems with clearly defined trust boundaries; leading complex investigations while improving engineering practices and operational readiness; mentoring engineers and providing direction through design and code reviews; and partnering with product and research teams to contribute to technical strategy and longer-term architecture.
You should thrive in ambiguity and act like an owner with a bias for action. You are a problem-solver who loves running toward challenges and is laser-focused on finding solutions. You are a high-trust collaborator ambitious for the team, embracing a challenge culture with candid feedback. You have a true growth mindset and are obsessed with your own development.
Required qualifications: 7+ years of software engineering experience including ownership of complex production systems and demonstrated ability to lead technically ambiguous, cross-functional projects; deep expertise in systems engineering, distributed systems, security engineering, backend platforms, or endpoint software with strong proficiency in Go, Rust, and Python; experience designing systems with clear security, privacy, and reliability requirements; foundational understanding of AI/ML technologies and experience leveraging or securing AI-driven solutions; and experience managing cloud infrastructure on AWS, GCP, or Azure.
Preferred qualifications include experience building security, cloud, or enterprise software including endpoint software for Windows, macOS, and Linux; familiarity with AI applications, agents, developer platforms, or AI security; and experience with security policy, detection, analysis, or software supply-chain systems.
