Sr. Detection Engineer

Company Overview

Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM).

What you'll do

Docusign is seeking a skilled and motivated Sr. Detection Engineer to join our Threat Detection Engineering team. Reporting to the Manager of Threat Detection Engineering, you will be a key contributor in architecting, building, and maintaining Docusign's threat detection capabilities.

This role is focused on architecting and engineering threat-driven detection logic, leveraging strict Detection-as-Code and software development principles. You will co-architect the design, development, and reliability of the underlying data pipeline and SIEM platform. You will build and deploy scalable, automated detection and response services that ensure robust protection across our cloud, on-premise, and endpoint environments. This role requires a strong software engineering foundation, a focus on system reliability, the ability to support services on-call, and a passion for architecting the critical infrastructure that powers our detection efforts.

This position is an individual contributor role reporting to the Sr. Manager, Threat Detection Engineering.

Responsibility

• Participate in the design, ownership, and support of the security data pipeline and SIEM platform which involves working with data collection, ingestion, processing, and storage of security telemetry
• Contribute to optimizing the platform for performance, scalability, and reliability to support all threat detection needs
• Design, develop, and implement high-fidelity threat detections based on threat intelligence, attacker TTPs, and analysis of security telemetry
• Focus on creating detections that are effective, accurate, and minimize false positives
• Embrace and implement Detection-as-Code principles throughout the detection lifecycle including using version control, automated testing, and continuous integration/continuous deployment (CI/CD) pipelines for detections to ensure consistency, reliability, and scalability
• Collaborate with the Incident Response team to translate threat intelligence into actionable detections with automated response workflows
• Participate in post-incident reviews to drive continuous improvement in detection capabilities
• Contribute to the adoption and integration of new detection technologies, frameworks, and processes
• Help architect and maintain scalable, automated security discovery and containment systems leveraging modern data platforms, EDR, network traffic analysis tools, and cloud-native security solutions
• Partner effectively with engineering, product, and other security teams to ensure comprehensive coverage, address blind spots, and instill security monitoring best practices throughout the software development lifecycle
• Contribute to establishing and authoring repeatable and scalable processes around detection and automation engineering
• Define and track key performance indicators to measure the effectiveness of detection capabilities
• Communicate technical security concepts, findings, and recommendations clearly and concisely to both technical and non-technical stakeholders

What you bring

Basic Qualifications

• 8+ years of progressive experience in cybersecurity, with at least 2+ years in a dedicated threat detection engineering role
• The individual must be a U.S. Citizen, U.S. National or U.S. Person. Individuals outside of these categories are generally barred from having logical access to IL5 data or infrastructure
• Experience with the design, implementation, and support of security data pipelines and SIEM platforms. Experience configuring SIEM platforms such as Microsoft Sentinel via Infrastructure-as-Code (e.g. Terraform) is a significant advantage
• Experience in developing threat detections at scale in cloud-inclusive environments (e.g., AWS, Azure, GCP)
• Experience with data pipeline technologies and architectures, including data extraction, transformation, loading, processing, and storage for security data, with hands-on experience managing and optimizing these systems
• Experience with the cyber threat landscape, attacker tactics, techniques, and procedures (TTPs), and frameworks such as MITRE ATT&CK
• Experience with detection rule languages (e.g., SPL, KQL) and advanced query development, with an understanding of the underlying data structures and query optimization
• Experience writing detections based on diverse security signals and telemetry (e.g., network traffic, endpoint logs, cloud logs), with an engineering approach to signal processing and analysis
• Experience with security tools and technologies such as SIEM/SOAR platforms (e.g., Splunk, Sentinel), EDR, IDS/IPS, network traffic analysis tools (e.g., Zeek, Suricata, Yara), and cloud security solutions, with an understanding of their architecture and integration
• Experience with scripting/programming (e.g., Python, Go, Bash, PowerShell) for security tooling, automation, and API integrations, with a focus on writing clean, maintainable, and efficient code
• Experience analyzing and interpreting large datasets and logs to identify security risks and events, applying data engineering and analysis techniques
• Experience with CI/CD pipelines and Detection-as-Code practices, including version control, testing, and automated deployment of detections
• Experience with AI and Machine Learning applications in threat detection and security, including the ability to evaluate, implement, and manage AI-based detection solutions and secure AI/ML systems

Preferred Qualifications

• Bachelor's degree or equivalent experience in Computer Science, Cybersecurity, or a related field; advanced degree or security certifications (e.g., GIAC, CISSP)
• Strong analytical and problem-solving skills, with meticulous attention to detail and an engineering approach to root cause analysis
• Experience with anomaly detection, machine learning, and statistical analysis of user behavior patterns for security purposes
• Background in security-focused software engineering or offensive security
• History of speaking at security conferences or publishing research
• Proven ability to collaborate effectively across cross-functional teams
• Passion for continuous learning, operational excellence, and a proactive, adversarial mindset, with a commitment to improving engineering processes and outcomes

Key skills/competency

• Threat Detection
• SIEM Platforms
• Data Pipeline Engineering
• Detection-as-Code
• Cloud Security (AWS, Azure, GCP)
• MITRE ATT&CK Framework
• Python/Scripting
• Incident Response Collaboration
• Security Telemetry Analysis
• CI/CD for Detections