Practice Customer Engineer, SLED Security, Google Public Sector

Identify and qualify business opportunities alongside the team, understanding key customer technical objections, and developing the strategies to resolve technical blockers.Deliver in-depth security and compliance expertise to support the technical relationship with Google’s customers, including product and solution briefings, proof-of-concept work, while partnering directly with product management to prioritize solutions impacting customer adoption to Google Cloud and security offerings.Demonstrate and prototype integrations with Google Cloud products directly in customer and partner environments.Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution on Google Cloud.Travel to customer sites, conferences, and other related events as required.Minimum qualifications:Bachelor's degree or equivalent practical experience.10 years of experience with cloud security architectures in a customer-facing or support role.Experience with security matters (e.g., encryption, identity management, access control, Security Information and Event Management (SIEM) platforms, Cloud Native Application Protection Platform (CNAPP) platforms, or network security).Experience engaging with, and presenting to, technical stakeholders or executive leaders.Experience with Generative AI, large language models (LLMs), or conversational AI systems, especially in the development of AI agents or agentic frameworks.Preferred qualifications:Master's degree in Computer Science, Engineering, Mathematics, a related technical field, or equivalent practical experience.Experience with security-related compliance standards (e.g., ISO 27001, NIST).Experience with Google Cloud Security platforms.Ability to script or code to automate security tasks (e.g., Python, Bash).Excellent communication and presentation skills.As a Security Customer Engineer (CE) for Google Public Sector, you will be the primary technical partner and trusted advisor to government and educational customers. You will work at the intersection of cybersecurity and cloud transformation, partnering with technical sales teams to differentiate Google Cloud through deep subject matter expertise.You will understand the mission issues and architect cross-pillar cloud solutions that solve them. You will lead the technical engagement, from initial high-level conversations with agency leaders to proofs-of-concept and architectural design. You will be responsible for driving the "technical win," ensuring customers understand the power of Google’s Unified Security portfolio and have a clear path to successful consumption and deployment.Google Public Sector brings the magic of Google to the mission of government and education with solutions purpose-built for enterprises. We focus on helping United States public sector institutions accelerate their digital transformations, and we continue to make significant investments and grow our team to meet the complex needs of local, state and federal government and educational institutions.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $152000 - $222000 (USD) + 42.86% bonus target + equity + benefitsLearn more about benefits at Google.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Reston, VA, USA; Washington D.C., DC, USA.Bachelor's degree or equivalent practical experience.10 years of experience with cloud security architectures in a customer-facing or support role.Experience with security matters (e.g., encryption, identity management, access control, Security Information and Event Management (SIEM) platforms, Cloud Native Application Protection Platform (CNAPP) platforms, or network security).Experience engaging with, and presenting to, technical stakeholders or executive leaders.Experience with Generative AI, large language models (LLMs), or conversational AI systems, especially in the development of AI agents or agentic frameworks.