Design, deploy, and operate production-scale ML systems that protect Copilot experiences, ensuring high reliability, performance, and security at global scale, targeting threats such as prompt injections, adversarial inputs, and agentic workflow abuse. Develop adaptive detection and policy models that are capable of learning from evolving attacker behavior to offer durable protection against emerging AI security threats. Build and own evaluation frameworks for AI security, including adversarial testing, red teaming support, and continuous robustness measurement across real Copilot scenarios. Define success metrics and conduct rigorous experimentation to quantify security effectiveness, adversarial robustness, precision/recall tradeoffs, and user experience impact. Partner with security and engineering teams to integrate ML defenses into secure orchestration frameworks that govern agent delegation, tool calling, and action execution. Monitor and analyze telemetry to improve model performance, reduce false positives/negatives, and guide iterative defense improvements. On-call Engineering Duties. Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python These requirements include but are not limited to the following specialized security screenings: Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Experience designing, building, and operating security critical software systems in production, including responsibility for correctness, availability, performance, and long term maintainability. Experience in threat modeling efforts for complex, distributed systems and driving mitigations from design through production deployment. Experience identifying, analyzing, and remediating security vulnerabilities in collaboration with security response, red team, or incident response partners. Experience building or contributing to security defenses such as enforcement layers, guardrails, detection, monitoring, or evaluation tooling in production environments. Experience working with distributed systems, including service to service communication, identity, authorization, telemetry, and failure isolation. Experience serving as a technical lead or architectural reviewer for security sensitive systems across multiple services or teams. Experience conducting vulnerability research, red teaming, or adversarial testing, including identifying novel or emerging attack classes. Experience participating in or leading incident response, post incident analysis, and translating incidents into durable, reusable security improvements. Experience designing reusable, platform level security solutions that eliminate classes of vulnerabilities rather than one off fixes. Experience establishing or operating risk management frameworks, including maintaining risk registries, defining mitigation priorities, and tracking measurable risk reduction. Experience building or operating security metrics, dashboards, or evaluation pipelines that demonstrate real world security impact. Experience mentoring senior engineers through design reviews, threat model coaching, or architectural guidance. Experience securing AI driven, agentic, or tool invoking systems, including prompt based architectures or orchestration layers. Experience communicating security architecture decisions and tradeoffs to engineering leadership, PM/TPM, and executive stakeholders. Ability to operate effectively in highly ambiguous, fast‑evolving security environments, particularly those involving autonomous or generative AI systems.