We are looking for engineers who not only have deep technical acumen but are driven by purpose and impact. This role is ideal for someone who enjoys tackling massive-scale infrastructure challenges and is motivated to protect users at the platform level.
As part of this high-impact engineering team, you will help build systems that process hundreds of billions of signals daily in real time. These systems power decision engines that enforce policy and ensure that the digital experiences we offer remain secure, reliable, and free of harmful content.
What You’ll Be Doing
- Designing and building ultra-low-latency, high-throughput distributed pipelines that process user signals and content metadata at global scale handling spiky workloads with seamless elasticity.
- Developing and optimizing core infrastructure components such as real-time rule execution engines, signal aggregators, and policy enforcement APIs that drive automated and human decision-making workflows.
- Collaborating with Machine Learning engineers to integrate scalable inference capabilities while keeping the system architecture modular, maintainable, and cost-effective.
- Continuously enhancing system resilience, observability, fault tolerance, and horizontal scalability to ensure 24/7 availability.
- Driving architecture and design discussions, leading technical reviews, and mentoring fellow engineers to shape the long-term evolution of the platform.
- Pioneering new engineering practices, performance tuning techniques, and deployment strategies that improve reliability and system quality.
Required Qualifications
- Bachelor’s degree in Computer Science or a related field or equivalent practical experience.
- 4+ years of professional software engineering experience building backend infrastructure or distributed systems.
- Solid command of programming languages such as C++, C#, or Java, and expertise in object-oriented design, multithreading, and systems architecture.
- Proven experience designing performance-critical backend systems, with a strong focus on scalability, reliability, and efficiency.
- Experience with stream processing or event-driven systems using frameworks such as Apache Flink, Kafka Streams, or Beam.
- Familiarity with modern, cloud-native data infrastructure Kubernetes, Azure, Delta Lake, BigQuery, Cosmos DB, etc.
Other Requirements
Preferred Qualifications
- Hands-on experience operationalizing Machine Learning inference at scale in a production environment.
- Passion for security, privacy, and digital trust.
- Experience contributing to open-source data processing or systems frameworks is a plus.
Why Join Microsoft
At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. That includes our employees. We are committed to building a diverse, inclusive, and respectful workplace where everyone can grow and thrive. You’ll have access to cutting-edge technology, ongoing learning and development, and a team that’s just as passionate about making a difference as you are.
This is your opportunity to make real-world impact on how digital safety is enforced at a massive scale, protecting communities while solving some of the hardest systems engineering problems in tech.