Autonomous Security Operations Engineer: AI-Driven Defense

Deriv

Dubai

On-site

AED 420,000 - 660,000

Full time

12 days ago
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Job summary

Deriv is building an autonomous security operations platform that hunts proactively, responds automatically, and learns continuously. In production, we already deploy automated security reviews on every PR and fraud models running in real time.

Join a security team protecting a distributed system processing transactions 24/7, enforcing Zero Trust, and maturing cloud configurations across AWS, GCP, and Azure. You’ll lead detection, response, and hardening at scale.

Qualifications

  • 8+ years in security operations or blue team work.
  • You can write custom detection rules and tune thresholds to reduce false positives.
  • You automate repetitive tasks with Python, Bash, or Terraform.
  • You have experience with ML-based anomaly detection or UEBA.
  • You have secured cloud environments at scale (AWS, GCP, or Azure).

Responsibilities

  • Develop early-detection logic by extending SIEM rules and AI baselines.
  • Run threat hunts using behavior analytics, log forensics, and threat intel.
  • Tune EDR/XDR configurations to reduce noise and improve attack visibility.
  • Lead automation of incident response with runbooks and workflows.
  • Collaborate with engineering to integrate security controls into CI/CD pipelines.

Skills

Security operations
Threat hunting
Incident response
Automation scripting (Python/Bash/Ter​
Cloud security (AWS/GCP/Azure)

Tools

SIEM
EDR/XDR
Okta
Azure AD
Terraform

Job description

Deriv is building an autonomous security operations platform that hunts proactively, responds automatically, and learns continuously. In production, we already deploy automated security reviews on every PR and fraud models running in real time.

Join a security team protecting a distributed system processing transactions 24/7, enforcing Zero Trust, and maturing cloud configurations across AWS, GCP, and Azure. You’ll lead detection, response, and hardening at scale.

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