AI Incident Response Analyst - Remote & Flexible

Alignerr Corp.; Madrid; Remote; EUR 34,000 - 62,000; Part time

Benefits offered by this job

Fully remote

Flexible schedule

Freelance perks: autonomy and global协作

Job summary

Alignerr is seeking an Incident Response Analyst to help train AI systems by evaluating AI-generated security responses. The role is remote, hourly, and offers flexible scheduling for 10–40 hours per week.

Candidates bring 2+ years in SOC/IR, hands-on SIEM experience, and strong feedback skills. You will analyze real and simulated incidents, validate detection rules, and provide actionable insights to improve AI accuracy.

Qualifications

• 2+ years of experience in SOC, incident response, or security operations.
• Hands-on experience with SIEM platforms, alert queues, and investigation tooling.
• Strong ability to triage and prioritize—separating meaningful threats from noise.
• Clear written communication skills for structured feedback.
• Comfortable working independently on task-based assignments.

Responsibilities

• Analyze realistic security events, alerts, and incident cases to evaluate AI-generated responses.
• Assess impact, root cause, and appropriate remediation steps for simulated incidents.
• Review and validate detection rules, alerting pipelines, and investigative playbooks.
• Identify gaps where AI-generated analysis diverges from real-world security operations.
• Provide structured, expert feedback that directly improves AI accuracy and reliability.
• Work independently and asynchronously on your own schedule.

Skills

SOC/IR experience

SIEM platforms

Investigation tooling

Threat triage

Written communication

Independent work

Job description

Alignerr is seeking an Incident Response Analyst to help train AI systems by evaluating AI-generated security responses. The role is remote, hourly, and offers flexible scheduling for 10–40 hours per week.

Candidates bring 2+ years in SOC/IR, hands-on SIEM experience, and strong feedback skills. You will analyze real and simulated incidents, validate detection rules, and provide actionable insights to improve AI accuracy.