Senior Software Engineer

Microsoft

HybridPosted July 29, 2026

About the role

Overview Microsoft Security (MSEC) is seeking a Senior AI Engineer to lead the development of AI-native, multi-agent systems that help customers securely adopt AI at an enterprise scale. This role sits at the intersection of AI engineering, security, and customer readiness, bridging the gap between cutting-edge AI capabilities and real-world enterprise adoption. You will design, build, and deploy intelligent systems that transform signals across identity, devices, data, applications, and infrastructure into actionable intelligence, automation, and measurable outcomes. You will operate in a highly collaborative, cross-company environment, driving end-to-end execution—from AI model development and data pipelines to production deployment, telemetry, and continuous optimization—while shaping how enterprises prepare for and securely adopt AI.

Senior Software Engineer

Microsoft

HybridPosted July 29, 2026

About the role

Overview Microsoft Security (MSEC) is seeking a Senior AI Engineer to lead the development of AI-native, multi-agent systems that help customers securely adopt AI at an enterprise scale. This role sits at the intersection of AI engineering, security, and customer readiness, bridging the gap between cutting-edge AI capabilities and real-world enterprise adoption. You will design, build, and deploy intelligent systems that transform signals across identity, devices, data, applications, and infrastructure into actionable intelligence, automation, and measurable outcomes. You will operate in a highly collaborative, cross-company environment, driving end-to-end execution—from AI model development and data pipelines to production deployment, telemetry, and continuous optimization—while shaping how enterprises prepare for and securely adopt AI.

Responsibilities AI Systems, Models & Platform Engineering - Design and build multi-agent AI systems leveraging LLMs, RAG pipelines, and vector-based retrieval to operationalize readiness across security domains. - Develop and productionize machine learning and deep learning models that transform large-scale, multi-source enterprise signals into contextual intelligence and automation. - Architect scalable systems for data ingestion, feature engineering, and model training, integrating signals across Microsoft services. - Implement optimization and automation algorithms for prediction, prioritization, and decision-making across AI readiness workflows.

Data, MLOps & Productionization - Build scalable data pipelines, ETL workflows, and train

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Responsibilities AI Systems, Models & Platform Engineering - Design and build multi-agent AI systems leveraging LLMs, RAG pipelines, and vector-based retrieval to operationalize readiness across security domains. - Develop and productionize machine learning and deep learning models that transform large-scale, multi-source enterprise signals into contextual intelligence and automation. - Architect scalable systems for data ingestion, feature engineering, and model training, integrating signals across Microsoft services. - Implement optimization and automation algorithms for prediction, prioritization, and decision-making across AI readiness workflows.