Detection Engineering Lead – Taiwan

Obsidian Security is the leading SaaS security platform trusted by global enterprises like Snowflake T-Mobile and Algolia. We protect 200 organizations across North America Europe the Middle East Southeast Asia Australia and New Zealand including many of the worlds largest Fortune 1000 and Global 2000 companies.

Founded in 2017 and backed by top investors like Greylock Obsidian was built to close a critical gap: securing SaaS apps where business happensMicrosoft 365 Salesforce and hundreds more. The company does this by offering a complete SaaS security platform to reduce risk detect and respond to threats and prevent breaches at the source. Obsidian was built by leaders who redefined endpoint and identity security at CrowdStrike Okta Cylance and Carbon Black. Now theyre transforming how SaaS is secured.

With AI driving rapid SaaS growth and complexity agentic AI tools gain privileged access to sensitive data through integrations creating new risks most security tools miss. Obsidian uniquely detects anomalous OAuth token activity and manages integration risks. Major announcements are on the horizon. Recognizing that SaaS security needs to evolve Obsidian enables growing organizations to start with a lightweight prevention-focused browser extension and expand coverage over time.

With global momentum a growing partner ecosystem including SentinelOne Databricks and Google Cloud and a major fundraise ahead Obsidian is scaling rapidly toward long-term growth and IPO readiness.

Obsidian Security is looking for a Detection Engineering Lead to establish and lead detection engineering capabilities within our growing Taiwan organization.

You will lead the development of security detections that identify identity threats malicious activity risky behavior and emerging attack patterns across cloud and SaaS environments. The role combines threat research detection modeling data analysis rule authoring and production engineering.

You will work closely with Security Research Product Management platform engineering data engineering and Customer Success to translate real-world threats into accurate explainable and operationally effective detections.

This is a hands-on leadership role. You will shape detection strategy and processes while directly contributing to threat models detection logic investigations and validation. You will also build and mentor a Taiwan-based team as the organization grows.

• Establish and lead the detection engineering function in Taiwan including its technical direction operating model quality standards and hiring plan.

• Research cloud identity and SaaS threats and translate attacker behaviors into actionable detection opportunities.

• Develop threat models covering attack paths adversary techniques identity misuse suspicious activity and control failures.

• Design author test and maintain detection rules and behavioral detection models.

• Define the telemetry enrichment correlation and historical context required to support effective detections.

• Partner with platform and data engineering teams to build scalable detection capabilities and production processing pipelines.

• Develop frameworks for detection testing simulation coverage measurement versioning release management and ongoing tuning.

• Measure and improve detection precision recall explainability performance and customer value.

• Investigate false positives and false negatives identify their root causes and improve detection logic and underlying data quality.

• Map detection coverage to relevant threat frameworks attack techniques product use cases and customer risks.

• Monitor the evolving threat landscape and rapidly develop coverage for new techniques and vulnerabilities.

• Partner with Product Management and Customer Success to understand customer environments workflows and detection requirements.

• Create clear documentation explaining detection intent supporting evidence expected behavior limitations and recommended response actions.

• Mentor detection engineers and security researchers while establishing a culture of scientific rigor curiosity and continuous improvement.

• Collaborate with teams across Taiwan the US the UK and Australia to build a unified global detection program.

• Significant experience in detection engineering threat research security analytics incident response threat hunting or a closely related security discipline.

• Experience leading security research or detection initiatives and mentoring other practitioners.

• Strong knowledge of attacker behavior identity threats cloud security and modern enterprise SaaS environments.

• Demonstrated experience developing production detections using rules queries correlations statistical methods or behavioral models.

• Experience working with large security datasets including audit events authentication activity identity data application logs or cloud telemetry.

• Ability to distinguish malicious behavior from legitimate activity and translate that reasoning into precise maintainable detection logic.

• Strong data analysis skills and proficiency with relevant query scripting or programming languages.

• Understanding of detection lifecycle management including research development validation deployment monitoring tuning and retirement.

• Experience measuring detection quality and using production feedback to improve security outcomes.

• Ability to communicate technical security concepts clearly to engineering product customer-facing and executive audiences.

• Strong written and verbal communication skills in English.

• Ability to collaborate effectively across regions time zones functions and cultures.

• Experience with identity security SaaS security cloud detection and response SIEM UEBA EDR or XDR products.

• Deep familiarity with identity-based attacks including account takeover session abuse privilege escalation persistence and lateral movement.

• Experience with MITRE ATT&CK or similar threat-modeling and coverage frameworks.

• Experience building detection-as-code systems rule languages detection engines or automated validation frameworks.

• Experience applying machine learning anomaly detection or generative AI to security problems.

• Experience investigating real-world intrusions or working directly with incident response teams.

• Experience building or scaling a detection engineering team.

• Experience working in Taiwan or with globally distributed APAC teams.

• Mandarin proficiency.

• Obsidian has a disciplined and scalable detection engineering capability in Taiwan.

• New threats are converted into production-quality detections quickly and reliably.

• Detection coverage quality and customer impact can be measured and continuously improved.

• False positives are controlled without sacrificing meaningful threat coverage.

• Detection engineers researchers and platform teams work through a clear and effective development lifecycle.

• Customers receive timely explainable and actionable security findings.