Senior/Software Engineer II - Agentic Security

Microsoft•Redmond, WA

About The Position

Microsoft Security represents a critical priority for customers facing digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aims to make the world a safer place by empowering users, customers, and developers with a security cloud offering simplified, end-to-end solutions. The Agentic Security Data Platform team builds and operates Microsoft’s next-generation security data platform, facilitating large-scale ingestion, storage, governance, and consumption of security and identity telemetry. The team develops scalable, reliable, and cost-efficient cloud-native services for security organizations and partners to onboard, access, analyze, and derive insights from high-volume security data. As a Software Engineer on the Data Platform team, you will contribute to designing, building, and modernizing services and ingestion pipelines for processing security data at scale. You will tackle challenging distributed systems and data platform problems, contributing to a unified platform powering Microsoft’s security products and enabling highly scalable, reliable, and efficient systems for security experiences across Microsoft. Microsoft's mission is to empower every person and organization to achieve more. Employees at Microsoft foster a growth mindset, innovate to empower others, and collaborate to achieve shared goals, building on values of respect, integrity, and accountability to create an inclusive culture.

Requirements

Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements.
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

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 OR equivalent experience.
Experience designing, building, and operating large-scale, distributed data pipelines or ingestion systems that process high-volume, continuous data streams.
Working knowledge of cloud infrastructure and services used to build scalable, production-grade ingestion systems.
Experience operating production services at scale, including monitoring, troubleshooting, and on-call/live-site support for distributed systems.
Experience with DevOps practices and continuous integration/continuous deployment (CI/CD), including building and maintaining automated build, test, and release pipelines for production services.
Experience leveraging new technologies, including AI-assisted development and tooling, to continuously improve engineering efficiency and quality.

Responsibilities

Collaborate with engineers, product managers, and customers to gather requirements, provide feedback, and deliver effective solutions.
Instrument data and develop key metrics to measure product usage, effectiveness, and customer satisfaction, enabling data-driven decision making.
Design, develop, and implement new identity management components, features, and platform enhancements.
Debug, troubleshoot, and resolve complex live site issues across compute, networking, storage, and distributed systems.
Partner with cross-functional teams to improve system reliability, scalability, performance, and operational excellence.
Analyze production telemetry and customer feedback to identify improvement opportunities and drive continuous enhancements.
Champion the adoption of modern engineering practices, including automated validation, safe and staged deployment strategies, continuous integration and delivery, and developer productivity tooling to increase both engineering velocity and operational confidence.
Actively leverage AI-assisted engineering tools throughout the software development lifecycle, including design, implementation, code review, testing, troubleshooting, and documentation, to improve productivity, code quality, and engineering effectiveness.