Senior Security Engineer, Threat Intelligence Group

Senior Security Engineer, Google Threat Intelligence Group

Maryland, USA. Remote eligible. This is not a fully remote position; 3-4 days each week onsite at Fort Meade, MD is required.

Note:

Google's hybrid workplace includes remote roles.
Remote location:
Maryland, USA.

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

• Bachelor's degree in Computer Science or a related technical field or equivalent practical experience.
• 5 years of experience with security assessments or security design reviews or threat modeling.
• 5 years of experience with security engineering, computer and network security and security protocols.
• 1 year of experience leading technical teams or leading technical risk analysis.
• Experience applying Cyber Threat Intelligence (CTI) methodologies to support monitoring, detection, and response capabilities within cyber security organizations.
• Possess an active TS/SCI security clearance with a full-scope polygraph.

• Experience in one or more of the following areas: malware reverse engineering, network forensics, threat hunting, or cloud security incident response.
• Understanding of AI/ML concepts (large language models (LLMs), predictive modeling, data pipelines) with the ability to discuss them fluently with both engineers and non-technical staff.

Our Security team works to create and maintain the safest operating environment for Google's users and developers. Security Engineers work with network equipment and actively monitor our systems for attacks and intrusions. In this role, you will also work with software engineers to proactively identify and fix security flaws and vulnerabilities.

In your capacity as a Security Engineer within the Google Threat Intelligence Group (GTIG) DoD Team, you will act as the lead onsite Mandiant authority for a client focusing on AI technologies. You will be tasked with connecting the domains of artificial intelligence and advanced cyber threat intelligence, gaining a deep understanding of the customer's specific AI‑related threat landscape to cultivate strong alliances between Google and client stakeholders.

Your routine responsibilities will include converting intricate technical data into customized, strategic intelligence that empowers our partners to effectively counter and respond to evolving AI‑driven cyber risks.

Part of Google Cloud, Mandiant is a recognized leader in dynamic cyber defense, threat intelligence and incident response services. Mandiant's cybersecurity expertise has earned the trust of security professionals and company executives around the world. Our unique combination of renowned frontline experience responding to some of the most complex breaches, nation‑state grade threat intelligence, machine intelligence, and the industry's best security validation ensures that Mandiant knows more about today's advanced threats than anyone.

Individual pay is determined by factors including job‑related skills, experience, and relevant education or training.

US: $174,000 - $253,000 (USD) + 15% bonus target + equity + benefits.

Learn more about benefits at Google.

• Identify, understand, and communicate critical threats and vulnerabilities unique to AI/ML systems, advocating for improved intelligence sharing across client and Google stakeholders.
• Produce tailored cyber threat intelligence reporting, including predictive analysis of future AI‑enabled threat scenarios and assessments of adversary AI use in the wild.
• Communicate complex technical findings regarding AI security threats, vulnerabilities, and incident response insights effectively to both technical and non-technical audiences.
• Foster cross‑functional collaboration with data scientists, engineers, analysts, and third‑party partners to address complex AI security challenges using industry best practices. Develop training materials and conduct knowledge transfer, including vulnerability detection workshops and train‑the‑trainer sessions for client personnel.
• Document detection logic, model architectures, and operational procedures, creating best practice guides for integrating AI‑driven detection into the Software Development Life Cycle (SDLC).