Senior Detection Engineer

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.

• Take complete accountability for your domain's health, backlog prioritization, and performance - serving as the ultimate point of contact for its overall efficacy
• Personally tackle the hardest detection challenges to establish design patterns, coding standards, and implementation blueprints for the rest of the team
• Define clear criteria for validated, tuned, and maintainable content, using design/code reviews and root-cause analyses to continuously eliminate false positives and missed threats
• Identify and actively drive the core numbers that define area health, including detection fidelity, ATT&CK coverage, false-positive/negative rates, and regression prevention
• Systematically translate input from threat intelligence, proactive threat hunting, and SOC analyst feedback into concrete roadmap priorities and continuous engine improvements

• Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain
• Deep detection experience in at least one of Endpoint (MDR), Cloud/SaaS, Identity, Email, or SIEM, and the judgment to own that area
• A track record of owning technical work end-to-end and being answerable for its quality without much oversight
• A strong grasp of how attackers operate, and fluent use of ATT&CK to decide where coverage should go
• Detector-as-code, version control, code review, and controlled deployment as the way you already work (Git, CI/CD)
• Experience leveraging AI-driven automation, LLMs, or machine learning models to accelerate detection engineering and threat analysis workflows (preferred)
• Programming/scripting (Python, Go, Ruby, etc.) to build detection tooling and automation beyond rule content (preferred)
• Reverse engineering or deeper malware analysis, where it's relevant to your domain (valued, not required)

• Various health plans
• Time off plans for vacation and sick time
• Parental leave options
• Retirement options
• Education reimbursement
• In-office perks