Splunk Engineer

Qualified person must have active DOE L, Q or DOD Top Secret. 

100% REMOTE

3. Qualifying individual “MUST” have the following skillsets:

·       Deep expertise in Splunk SPL, including advanced search commands, statistical functions, data models, and performance optimization

·       Hands-on experience with Splunk Enterprise Security, including correlation searches, risk-based alerting (RBA), notable events, and the ES framework

·       Working knowledge of the Splunk AI Toolkit (AITK) for building and applying ML-based detections

·       Experience with the Splunk App for Data Science and Deep Learning (DSDL), including custom model development and deployment

·       Strong understanding of the MITRE ATT&CK framework and detection engineering methodology

·       Familiarity with common attack techniques, log sources, and security data (EDR, network, cloud, identity, etc.)

4. Qualifying individual “NICE” to have the following skillsets:

·       Experience with detection-as-code practices and tools (Git, CI/CD pipelines)

·       Proficiency in Python for data processing and model development

·       Knowledge of SOAR platforms and detection automation

·       Relevant certifications (Splunk Certified Power User/Admin, Splunk Enterprise Security Certified Admin, GIAC, etc.)

·       Prior experience in a SOC, threat hunting, or incident response role

In this role, the selected candidate will design, build, and tune detections that identify malicious activity across our environment, working at the intersection of security analysis, data engineering, and machine learning. We’re looking for a candidate that lives and breathes Splunk and gets excited about turning raw telemetry into high-fidelity alerts, we want to hear from you.

What the candidate is expected to perform:

·       Design, develop, and maintain detection content using Splunk Search Processing Language (SPL) to identify threats across diverse data sources

·       Build and tune correlation searches, notable events, and risk-based alerting within Splunk Enterprise Security (ES)

·       Leverage the Splunk App for Data Science and Deep Learning (DSDL) to develop machine learning models for anomaly detection and advanced threat identification

·       Apply the Splunk App for Anomaly Detection and the Splunk AI Toolkit (AITK) to develop statistical and ML-driven detections that go beyond signature-based approaches

·       Map detection coverage to the MITRE ATT&CK framework and identify gaps in visibility

·       Collaborate with threat intelligence, incident response, and SOC teams to translate emerging threats into actionable detections

·       Reduce false positives and alert fatigue through continuous tuning and detection lifecycle management

·       Develop and maintain detection-as-code workflows, including version control, testing, and CI/CD for detection content

·       Create documentation, runbooks, and detection specifications to support downstream analysts