About The Position

Mars Security is an early-stage cybersecurity company building a platform that helps security teams conduct continuous threat hunting and detection engineering across their existing technology stack. The company is seeking a Detection & Response Engineer to work across detection engineering, incident response, and threat hunting. The engineer will design, test, and tune detection logic in real customer environments, investigate the activity it surfaces, and use findings to improve security coverage. The role involves working directly with founders and customers, with contributions shaping the product.

Requirements

  • At least 5 years of hands-on experience in a SOC, threat hunting, or detection engineering.
  • Detection engineering experience, including writing rules that have caught real attacks.
  • Incident response experience involving investigation, scoping, containment, and root-cause analysis.
  • Strong query skills across detection languages such as SPL, KQL, Sigma, and YARA.
  • Solid understanding of attacker TTPs, MITRE ATT&CK, and how campaigns operate end to end.
  • Familiarity with networking, identity, cloud, and endpoint infrastructure.
  • Proficiency in Python for scripting, automation, and analysis.
  • Excellent written and verbal English communication skills.
  • Strong customer-facing skills and the ability to build trusted customer relationships.
  • Team-oriented approach with strong collaboration and communication skills.

Nice To Haves

  • Experience with detection-as-code, CI/CD for detections, or SOAR.
  • Background in malware analysis, threat intelligence, or red teaming.

Responsibilities

  • Design, build, and validate detection rules across SIEM, EDR, cloud, and identity environments.
  • Map detection coverage against attacker TTPs and active campaigns, and close important coverage gaps.
  • Tune detections to reduce noise and false positives without losing meaningful signal.
  • Investigate and triage alerts and suspicious activity, and support incident response in customer environments.
  • Conduct hunts to identify activity missed by existing detections and turn findings into new detection content.
  • Build response playbooks and automation to shorten the time from detection to containment.
  • Contribute to the platform by defining effective detection and response at scale.
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