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Azure SRE teams strive to improve reliability fundamentals via software engineering, preferring long-lasting platform improvements delivered as engineering projects over repetitive manual operations. We contribute to the product fundamentals and architecture, share knowledge, and code, and prefer reuse over re-invention, always looking for ways to make what we build useful to multiple teams and products.

We are not looking for people who know it all, we are looking for people who want to learn it all. We value the input of people who arent afraid to learn all the time and embrace mistakes as they continuously improve both our services and themselves. If you are excited by this type of challenge and you love to work in groups of people who are similarly excited: come join us!

Responsibilities
Collaborate with stakeholders to identify user requirements, incorporating feedback and actionable metrics into future designs.
Contribute to product architecture, helps create proposals, owns solutions, and ensures security and compliance. Assist in testing plans and automation features.
Implement code for products, services, or features with a focus on extensibility and maintainability. Review code for quality, reliability, and adherence to coding standards.
Execute project plans, break down work items, conduct experimentation, and support safe deployment of features.
Manage live service operations, act as a DRI on call, integrates telemetry data, and contributes to data analysis for system health.
Engineering Excellence: Improve developer tools, contribute to automation in production, ensure compliance with security and privacy, and stay current with industry developments.
Maintain communication with key partners across the Microsoft ecosystem to achieve desirable user experiences and meet the dynamic needs of partners and customers through product development.

Azure SRE teams strive to improve reliability fundamentals via software engineering, preferring long-lasting platform improvements delivered as engineering projects over repetitive manual operations. We contribute to the product fundamentals and architecture, share knowledge, and code, and prefer reuse over re-invention, always looking for ways to make what we build useful to multiple teams and products.

We are not looking for people who know it all, we are looking for people who want to learn it all. We value the input of people who arent afraid to learn all the time and embrace mistakes as they continuously improve both our services and themselves. If you are excited by this type of challenge and you love to work in groups of people who are similarly excited: come join us!

Responsibilities:
Partner across multiple product groups to apply subject-matter expertise in distributed systems design practices, interactions between cloud technology layers and components, basic dependencies at scale, and the code that defines infrastructures.
Lead by example and mentors others to produce extensible and maintainable code used across products.
Develop and evangelize insights, best practices, and standards that can be applied to improve system, platform, and/or product development and operations across the business.
Drive continuous improvements in the architecture, code, features, operations and comprehensive use scenarios of products by leveraging end-to-end technical expertise.
Make improvements to the product fundamentals and architecture, share knowledge and code, always looking for ways to make what we build useful to multiple teams and products. 
Demonstrates end-to-end expertise in distributed systems design, interactions between cloud technology layers.
Provide technical leadership in test maturity reviews, static analysis reviews, meetings, on-call rotations, and incident responses throughout product development and operations cycles.
Provides deep business and technical expertise as required to resolve major incidents.

Do you want to be a Data Scientist on an elite Data Science team? Do you want to build Data Analytics for a global Security Product? Do you want your work to be impactful on millions of users?

Join us and become part of a winning Data Science team that builds the brain of one of our most exciting security products, our Defender for Endpoint (MDE). As cyber-attacks have become more sophisticated, MDE helps enterprises detect, investigate, and automatically disrupt advanced attacks and data breaches on their networks. Our team is responsible for developing and deploying Machine Learning (ML) models that protect organizations worldwide and owning Data Analytics systems that facilitate data-driven decisions and operational excellence.

If you are a talented Data Scientist with excellent analytical, statistical, and data-visualization skills, who is passionate about applying Data Science to drive a revolutionary cyber-security product, we would like to talk to you!

Responsibilities:
Collaborate with Security experts and other stakeholders to define Business metrics.
Work with data engineers to implement these metrics over Big Data sources.
Create and maintain dashboards and visualizations.
Conduct data analysis and present insights to the leadership team and stakeholders.
Develop Anomaly Detection and monitoring solutions to ensure operation excellence of AI and other systems in MDE.

Do you want to be a Senior Data Engineer on an elite Data Science team? Do you want to build data solutions that power AI and Data Analytics of a global Security Product? Do you want your work to be impactful on millions of users?

Join us and become part of a winning Data Science team that builds the brain of one of our most exciting security products, our Defender for Endpoint (MDE). As cyber-attacks have become more sophisticated, MDE helps enterprises detect, investigate, and automatically disrupt advanced attacks and data breaches on their networks. Our team is responsible for developing and deploying Machine Learning (ML) models that protect organizations worldwide and owning Data Analytics systems that facilitate data-driven decisions and operational excellence.

Responsibilities:
Create and maintain robust Big Data pipelines for Analytics and ML systems.
Optimize performance of Big Data scripts and queries.
Create monitoring and reporting infrastructure.
Develop systems that facilitate Data Science activities such as Analytics and Feature Extraction.