Endpoint Engineer (C++ / Systems) (Remote, Full-Time) [AS349]

About Smart WorkingAt Smart Working, we believe your job should not only look right on paper but also feel right every day. This isn’t just another remote opportunity - it’s about finding where you truly belong, no matter where you are. From day one, you’re welcomed into a genuine community that values your growth and well-being. Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles. We help you discover meaningful work with teams that invest in your success, where you’re empowered to grow personally and professionally.Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world.About the RoleAs an Endpoint Engineer (C++ / Systems), you will be responsible for developing reliable, high-performance endpoint sensing capabilities for an AI-native cybersecurity platform. This mid-to-senior-level position requires strong computer science fundamentals, independent technical ownership and a commitment to engineering quality.You will work within a team of 14+ engineers across Backend, DevOps, Endpoint, Frontend and Design, reporting to the VP of Engineering and AI. The team operates with a flat structure, where each engineer takes ownership of their discipline within a project.This is a remote opportunity aligned with UK working hours, suited to an engineer who thrives on technical challenges, uses AI tools confidently and takes responsibility for delivering solutions that solve real customer problems.ResponsibilitiesDevelop and maintain a C++17 endpoint sensor running on customer machines across Windows, Linux and macOSCapture, process and stream host and network telemetry while maintaining a minimal system footprintEnsure memory safety, thread safety and graceful failure handling, particularly on customer machines where redeployment is challengingContribute to the development of a virtualized testing environment capable of running attack scenarios across multiple operating systems as a likely early projectMaintain high standards of software correctness, performance, reliability and testing to minimize risks across large-scale customer deploymentsTake end-to-end ownership of engineering features and projects, from understanding customer requirements through to successful deliveryWork directly with customers to understand technical challenges and ensure solutions effectively address their needsIndependently establish priorities and manage two major projects alongside smaller AI-driven engineering tasksUse AI agents and frontier models daily to accelerate development, explore unfamiliar technologies and navigate complex codebasesCollaborate closely with engineering colleagues, maintaining clear communication while working autonomouslyPrioritize high-impact engineering work and respond quickly to critical requirementsDemonstrate a growth mindset by welcoming feedback, reconsidering existing solutions and contributing to continuous team improvementBuild trust through careful engineering, transparent communication, early identification of risks and consistent deliveryRequirementsMinimum 5 years of professional software engineering experience, preferably involving systems programming or low-level software developmentMinimum 4 years of hands-on experience with modern C++, including strong proficiency in C++17Minimum 3 years of experience in systems programming, with strong computer science fundamentals covering operating system internals, kernel responsibilities and memory managementMinimum 3 years of experience with multithreading, concurrency and thread safety in performance-sensitive applicationsMinimum 3 years of experience in memory management and memory safety, including developing reliable and resource-efficient softwareMinimum 3 years of experience in performance optimization, particularly within systems-level applicationsMinimum 3 years of experience in software testing and correctness, with a rigorous approach to reliability and failure handlingDaily, hands-on experience using AI agents and frontier AI models to support software engineering, solve unfamiliar technical problems and work independently across different codebasesDemonstrated ability to use LLMs to learn unfamiliar technical areas and manage multiple engineering projects effectivelyStrong understanding of engineering reliability and the potential impact of software failures on customer systemsProven ability to take ownership of engineering projects from beginning to end, independently setting priorities and delivering outcomes without constant supervisionCustomer-focused approach, with the willingness to communicate directly with customers and remain accountable until their problems are resolvedAbility to prioritize urgent, high-impact work while maintaining engineering qualityExcellent communication and collaboration skills, with a proactive approach to sharing progress, challenges and technical decisionsGrowth mindset, openness to constructive criticism and willingness to reconsider or replace existing solutions when necessaryCommitment to honesty, attention to detail, early identification of problems and consistent deliveryAbility to explain technical implementations, justify engineering decisions and demonstrate a clear understanding of developed solutionsWillingness to work remotely in alignment with UK working hoursCandidates with strong Windows systems experience are encouraged to apply. Previous Linux and macOS experience is not mandatory, as these can be learned. Prior cybersecurity experience is also not required.Nice to HaveExperience with packet processing or network sensingKnowledge of eBPF, kernel development or driver developmentExperience in endpoint security or Endpoint Detection and Response (EDR)Familiarity with CMake, Docker-based builds and cross-platform software deliveryExperience with Open Cybersecurity Schema Framework (OCSF) or OpenTelemetryPython programming experienceWe may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. 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