About the job
About Zscaler
Zscaler stands at the forefront of zero trust security, recognized as a global leader in safeguarding digital transformation. Major enterprises, critical infrastructure organizations, and government entities worldwide depend on Zscaler to secure their users, branches, applications, data, and devices. Our advanced Zscaler Zero Trust Exchange platform, supported by cutting-edge AI, counters billions of cyber threats and policy breaches daily, streamlining operations and enhancing productivity for modern enterprises.
At Zscaler, we prioritize impact over titles, fostering a culture of trust built on results. We embrace transparency and value constructive, honest debate, focusing on rapidly identifying the best ideas. Our high-performing teams are empowered to make swift and quality contributions. Our culture emphasizes customer obsession, collaboration, ownership, and accountability.
Embodying our “AI Forward, People First” philosophy, we strive for innovation and agility, empowering our employees to realize their full potential. If you are driven by purpose, excel at solving complex challenges, and aspire to make a global impact, we invite you to join Zscaler and help shape the future of cybersecurity.
Role
We are seeking a Senior Threat Researcher to join our Engineering team in Bangalore on a hybrid work model, reporting directly to the Director of Software Development Engineering.
In this role, you will be instrumental as a Threat Researcher within our Engineering team, contributing to the development and enhancement of the world’s largest cloud security platform. Your vision and expertise will empower organizations globally to leverage speed and agility through a cloud-first strategy.
What You’ll Do (Role Expectations)
- Lead the complete detection lifecycle by investigating emerging threats and tactics, techniques, and procedures (TTPs) to create refined, multi-platform detections while optimizing the Threat Detection Efficacy Matrix.
- Enhance detection capabilities through adversary emulation to uncover gaps and collaborate with cross-functional teams to test, validate, and bolster security controls.
- Design and operationalize innovative deception use cases, including those for AI infrastructure.
- Transform deception telemetry into actionable detections and automated response playbooks.
- Develop machine learning pipelines that enhance deception signals (context, asset criticality, identity risk, kill-chain stage), facilitating proactive security measures.

