Cyber Detection Engineer

Detection Engineer - Early Career

Role Overview:

The Detection Engineer supports the development, testing, tuning, and maintenance of cyber detection capabilities across the Security Operations Centre (SOC). Working closely with SOC analysts, threat intelligence, incident response, and engineering teams, this role helps improve visibility, detection accuracy, and response effectiveness. This is an early-career position designed for individuals looking to build expertise in detection engineering, SIEM content development, threat analytics, and automation. The successful candidate will demonstrate curiosity, analytical reasoning, and the ability to independently investigate why a detection fired, how an attack could occur, and how future detections can be improved.

Key Responsibilities:

• Support the development, testing, and maintenance of SIEM detection rules, analytics, alerts, and correlation logic.
• Assist with tuning existing detections to reduce false positives and improve detection quality.
• Investigate missed detections and support root-cause analysis activities.
• Work with SOC analysts to understand alert triage outcomes and improve detection content.
• Help onboard new log sources into monitoring platforms and validate data quality and coverage.
• Support detection use-case development using threat intelligence, MITRE ATT&CK, incident findings, and known attack techniques.
• Participate in threat hunting exercises and assist with developing new detection opportunities.
• Assist with maintaining detection engineering documentation, standards, playbooks, and testing records.
• Support development of automation workflows within SIEM, SOAR, and response platforms.
• Assist the SOC in the triage, investigation, and response of security alerts, incidents, and escalations.
• Contribute to purple-team, tabletop, and validation exercises to measure effectiveness of detections.
• Track detection performance metrics, including false positives, false negatives, detection coverage, and alert quality.
• Support continuous improvement activities following incidents, audits, and lessons learned reviews.
• Maintain flexibility to support global cybersecurity operations, including participation in management meetings, vendor engagements, support calls, incident response activities, and after-hours escalations across multiple time zones as needed.

Required Qualifications:

• Bachelor's degree in Cybersecurity, Computer Science, Information Technology, Engineering, or equivalent experience.
• 1-3 years experience in cybersecurity, IT operations, SOC operations, system administration, or related technical field.
• Understanding of cybersecurity fundamentals including phishing, malware, identity attacks, network attacks, and incident response.
• Knowledge of AI-assisted detection engineering, large language models (LLMs), agentic workflows, and security automation platforms used to improve analyst productivity and detection outcomes.
• Basic knowledge of SIEM platforms and log analysis concepts.
• Understanding of networking fundamentals including TCP/IP, DNS, HTTP, authentication, and firewalls.
• Strong analytical and problem-solving skills.
• Ability to learn quickly and work effectively within a collaborative team environment.
• Strong written and verbal communication skills.

Preferred Qualifications:

• Experience with SIEM/SOAR platforms, Microsoft Defender, Azure, AWS, or similar platforms.
• Experience developing, integrating, or operationalizing AI-powered analysis, automation, and agent-based workflows within security operations, incident response, or detection engineering functions.
• Knowledge of MITRE ATT&CK framework.
• Basic scripting experience using Python, PowerShell, KQL, or SQL.
• Security+, SC-200, AZ-500, CySA+, or equivalent certifications.
• Experience participating in labs, CTFs, internships, threat hunting, or cyber research projects.

Success Measures:

• Improvement in detection quality and reduction in false positives.
• Successful onboarding and validation of data sources.
• Delivery of new and enhanced detection use cases.
• Contribution to incident-driven detection improvements.
• Accurate documentation and testing of detection logic.