Senior Detection Engineer

Nightwing Technologies, LLC; Arlington (VA); On-site; USD 140,000 - 210,000; Full time

Job summary

Nightwing Technologies, LLC is seeking a Senior Detection Engineer to develop, validate, and tune detections for proactive threat hunting across federal and critical infrastructure environments. The role spans endpoint, network, identity, and cloud telemetry, serving as a bridge between threat hunters, delivery teams, engineers, and data scientists.

You will turn operational findings into validated detections, automation, and capability requirements, coordinating with various teams to improve

Qualifications

• must have hands-on experience turning threat intel and hunt findings into validated detections.
• knowledge of endpoint, network, identity, and cloud telemetry is essential.

Responsibilities

• Develop and test hypotheses to uncover persistence, privilege escalation, credential access, lateral movement, C2, and defense evasion.
• Build behavioral analytics, correlation rules, signatures, and queries across endpoint, network, identity, cloud telemetry.
• Translate hunt results into reusable detections with clear data requirements and guidance.
• Test detections against historical telemetry and simulations to verify behavior and reduce evasion opportunities.
• Coordinate with hunters, responders, analysts, and engineers to integrate detections into workflows.
• Maintain automation for enrichment, queries, and validation, including SOAR playbooks where applicable.

Skills

Threat hunting

Detection engineering

Endpoint telemetry

Network telemetry

Cloud telemetry

Automation scripting

Threat intelligence translation

Job description

Nightwing provides technically advanced full-spectrum cyber, data operations, systems integration and intelligence mission support services to meet our customers' most demanding challenges. Our capabilities include cyber space operations, cyber defense and resiliency, vulnerability research, ubiquitous technical surveillance, data intelligence, lifecycle mission enablement, and software modernization. Nightwing brings disruptive technologies, agility, and competitive offerings to customers in the intelligence community, defense, civil, and commercial markets.

Nightwing is supporting a U.S. Government customer to provide for onsite incident response to civilian Government agencies and critical asset owners who experience cyber-attacks, providing immediate investigation and resolution. Contract personnel perform investigations to characterize the severity of breaches, develop mitigation plans, and assist with the restoration of services. Nightwing is seeking a Senior Detection Engineer in support of this contract.

The Senior Detection Engineer develops, validates, deploys, and tunes detection logic supporting proactive threat hunting across federal and critical infrastructure environments. The role combines advanced threat hunting tradecraft, adversary behavior analysis, and detection engineering to identify sophisticated threats, close visibility gaps, and improve detection effectiveness.

The engineer translates threat intelligence, hunt findings, and incident response lessons into reliable behavioral analytics, investigative queries, and automation. This work moves the team beyond individual hunts toward faster, repeatable, and scalable operations. Working across endpoint, network, identity, and cloud telemetry, the engineer selects detection methods based on available evidence and mission requirements. The position serves as the technical bridge between threat hunters, technical delivery teams, system engineers, analytics developers, and data scientists, turning operational findings into validated detections, automation, sensing improvements, and actionable capability requirements.

Job Responsibilities

• Develop and test hypotheses to uncover persistence, privilege escalation, credential access, lateral movement, command and control, and defense evasion. Correlate evidence across data sources and document defensible conclusions.
• Build behavioral analytics, correlation rules, signatures, and queries using endpoint, network, identity, cloud, and application telemetry. Target adversary techniques and activity sequences rather than individual indicators of compromise.
• Convert validated hunt methods, incident findings, and exercise results into reusable detections. Document each detection's purpose, data requirements, investigative guidance, assumptions, and known limitations. Translate remaining gaps into technical requirements and acceptance criteria, recommend priorities through Threat Hunting governance, and verify that delivered capabilities meet the operational need.
• Test detections against representative malicious and benign activity using historical telemetry, controlled simulations, and purple team exercises. Verify intended behavior, evaluate evasion opportunities, and retain test evidence.
• Analyze false positives, false negatives, alert volume, thresholds, exclusions, and environmental baselines. Improve detection fidelity and alert context through enrichment and prioritization, while assessing the risk of suppressing legitimate threat activity.
• Assess the availability, reliability, and quality of sensors, tools, and data sources. Identify collection, parsing, normalization, and retention gaps and explain their impact on active hunts and production detections. Coordinate remediation with infrastructure teams and validate restored coverage.
• Develop and maintain automation for enrichment, query execution, analytical workflows, and detection validation, including SOAR playbooks where applicable. Tune data pipelines and queries for speed and responsiveness. Build in review, error handling, and recovery procedures.
• Maintain version-controlled content, peer reviews, release criteria, approval records, and rollback procedures. Revalidate analytics after platform, schema, environmental, or adversary tradecraft changes.
• Coordinate with hunters, incident responders, intelligence analysts, and platform engineers to integrate detections into investigative and automated workflows.
• Measure validated detection coverage, fidelity, actionable findings, and remaining gaps. Communicate the operational significance of technical findings and avoid equating rule counts with effective coverage.
• Partner with analytics developers and data scientists to develop and validate advanced analytics, including machine learning where appropriate. Assess operational value, false positives, data dependencies, and analytical limitations.
• Provide technical leadership supporting the section focal point for vulnerability management (VM)