Senior Security Engineer - Getting Customers Ready for AI

Microsoft•Redmond, WA

1d•$119,800 - $234,700

About The Position

Microsoft Security's Getting Customers Ready for AI team is seeking a Senior Security Engineer with deep domain expertise to build and operationalize security-first systems that enable safe and scalable AI adoption. This role sits at the intersection of security engineering, AI systems, and enterprise readiness, focusing on transforming complex signals across identity, endpoints, data, applications, and infrastructure into actionable security insights, detections, and automated mitigation workflows. You will design and build end-to-end security systems that detect, prioritize, and respond to risks in AI-enabled environments—bridging traditional security controls with emerging AI-native threat models (LLM abuse, prompt injection, data exfiltration, model misuse). You will operate in a highly collaborative environment, driving execution from security signal ingestion and detection engineering to response automation and governance, helping customers achieve secure AI readiness at enterprise scale.

Requirements

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#, Java, or Python OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
Microsoft Cloud Background Check: This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

8+ years of experience designing, building, and operating production-scale security systems, platforms, detections, or services within enterprise or cloud environments.
Experience in one or more security domains, such as identity, cloud, endpoint, or data security, including detection engineering, threat modeling, incident response, or related security practices.
Proficiency in software engineering and automation using languages such as Python, C#, Java, or similar technologies, with experience building distributed systems and large-scale data platforms.
Experience working with security telemetry, SIEM platforms, data lakes, or related technologies to support security analytics, monitoring, and detection.
Familiarity with AI/ML technologies and associated security considerations, including large language models (LLMs), retrieval-augmented generation (RAG), and agentic systems.
Experience securing enterprise-scale cloud services and infrastructure, preferably within Azure environments.
Demonstrated ability to collaborate across teams, navigate ambiguity, and communicate complex technical concepts to diverse technical and business audiences.

Responsibilities

Design and build detection pipelines across identity, endpoint, data, and application signals to uncover vulnerabilities, misconfigurations, and active threats.
Develop correlation engines and detection logic that combine multi-source telemetry into high-confidence security signals.
Build and operationalize end-to-end detection → validation → prioritization → remediation workflows.
Implement automated incident response and remediation playbooks leveraging rule-based systems, workflows, and AI-assisted reasoning.
Architect and build scalable security platforms and services that process high-volume enterprise telemetry.
Develop data pipelines and distributed systems for ingestion, enrichment, and real-time analysis of security signals.
Integrate security capabilities into APIs, services, and platform layers to enable reusable and extensible solutions.
Ensure systems are designed for reliability, performance, isolation, and security by design.
Build systems to discover and track vulnerabilities across cloud resources, identities, and application environments.
Develop prioritization models that incorporate exploitability, impact, and business criticality.
Enable workflows that drive end-to-end remediation closure, integrating with engineering systems and developer pipelines.
Align with frameworks such as Defender, MDC, ASPM to enable holistic risk visibility and response.
Define and implement controls for AI-specific threat vectors (prompt injection, data leakage, model abuse, adversarial inputs).
Build detection and mitigation mechanisms for LLM-based systems, RAG pipelines, and agentic workflows.
Embed security into AI system design, inference pipelines, and orchestration layers.
Contribute to responsible AI practices, governance, and secure deployment patterns.
Build rich telemetry systems to track security posture, risk signals, and system performance.
Develop analytics to measure detection effectiveness, false positives, and response outcomes.
Leverage telemetry to enable continuous improvement loops across detection and response systems.
Partner with Engineering, Product, Data Science, and Security teams to translate security problems into scalable engineering solutions.
Work across a matrixed organization to align signals, platforms, and response workflows.
Help define security readiness standards and onboarding playbooks for enterprise AI adoption.
Lead design and delivery of complex, large-scale security systems from concept to production.
Establish best practices for secure coding, system design, reliability, and governance.
Drive data-driven and evidence-based decision-making across security engineering initiatives.
Mentor engineers and elevate the organization’s security engineering maturity.
Embody our culture and values.