• AI-Driven Detection & Engineering: Leverage LLMs and machine learning to automate detection logic, summarize complex attack chains, reduce false positives, and accelerate the full detection development lifecycle using tools such as Capital One's Detection Engineering Assistant.

• Detection-as-Code (DaC) Leadership: Lead the design, development, and maintenance of detection rules using DaC methodologies, utilizing GenAI-assisted development workflows and CI/CD pipelines against the Cyber Detection Library (CDL).

• Behavioral Detection Engineering: Design and build high-fidelity behavioral detections that identify adversary patterns, TTPs, and anomalous endpoint activity — leveraging user and entity behavior signals, process telemetry, and correlation logic to distinguish malicious from benign activity at scale.

• Strategic Architecture: Utilize the MITRE ATT&CK framework to visualize, prioritize, and close endpoint coverage gaps; drive detection architecture decisions that balance fidelity, volume, and operational risk across the endpoint threat surface.

• Offensive Alignment & Threat Research: Apply a deep understanding of Red Team methodologies and adversary TTPs to conduct hypothesis-driven threat research across enterprise endpoint environments — translating attacker techniques into high-fidelity detections and proactively identifying coverage gaps before they are exploited.

• Endpoint Domain Ownership: Own end-to-end detection coverage for the Endpoint threat surface — managing the full lifecycle from telemetry onboarding through alert deployment, tuning, and continuous coverage gap analysis in collaboration with the Coverage Review Team.

• Stakeholder & Risk Management: Partner with business leaders, CSOC, Cyber Threat Intelligence, and Cyber Threat Hunt to ensure robust monitoring across endpoint environments while ensuring all documentation meets strict fintech compliance and audit standards.

• Technical Leadership & Mentorship: Serve as a technical bar-raiser across the team — mentoring engineers on traditional security concepts, emerging AI-driven workflows, and detection engineering best practices.

• Deep expertise in endpoint security, EDR platforms, and Windows, Linux, macOS telemetry analysis

• Previous experience on a detection engineering, threat detection, or detection operations team with a focus on endpoint threat surfaces

• Extensive experience with SQL and data querying at scale

• Strong understanding of attacker TTPs, Red Team methodologies, and translating offensive security insights into high-fidelity detections

• Experience with ML or data science concepts applied to security use cases (anomaly detection, behavioral analytics, risk scoring)

• Excellent analytical, communication, and cross-functional collaboration skills

• Ability to perform independent root cause analysis and convey complex security risks to both technical and executive audiences

• Demonstrated ability to mentor engineers and contribute to a culture of continuous improvement

• High School Diploma, GED, or equivalent certification

• At least 4 years of experience working in cybersecurity or information technology

• At least 4 years of experience with endpoint and host logs (Windows Event Logs, Sysmon, EDR telemetry)

• At least 2 years of experience with EDR platforms (CrowdStrike Falcon, SentinelOne, Microsoft Defender)

• At least 4 years of experience developing alerts for threat detection

• At least 2 years of experience with penetration testing, offensive security, or adversary emulation

• At least 1 year of experience with machine learning or data science applied to security

• Bachelor's Degree

• 6+ years of experience in Threat Detection, Threat Hunting, or Security Engineering

• 4+ years of experience with Python

• 4+ years of experience with data science concepts and techniques (anomaly detection or behavioral analytics)

• 2+ years of experience publishing code to GitHub using CI/CD workflows

• Experience with Databricks, Apache Spark, or streaming data platforms

• Experience with Detection-as-Code methodologies and YAML-based detection frameworks

• Experience with CrowdStrike Falcon (custom IOAs, detection tuning, telemetry analysis)

• Experience with Windows internals, process injection techniques, LOLBAS, and fileless attack detection

• Experience with endpoint forensics, malware triage, or adversary emulation exercises targeting endpoint environments

• 2 or more professional certifications (GCIA, GCIH, CISSP, GMON, GREM, GCTD, MLE, or AWS Cloud Practitioner, AWS Security)

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.