This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
CoreAI sits at the center of Microsoft’s mission to redefine how software is built and experienced, providing the foundational platforms, services, and developer experiences that power the next generation of AI-driven applications. As part of CoreAI, the Experimentation Platform (ExP) enables trustworthy, high-scale online experimentation that accelerates product learning and drives progress across Microsoft’s AI ecosystem. You will play a key role in helping teams ship better AI experiences faster by providing the experimentation capabilities needed to evaluate, refine, and safely deploy new innovations. In this role, you will help strengthen one of the highest-scale experimentation platforms - critical infrastructure that enables rapid iteration in AI systems and product features. You will contribute to services that empower engineers and scientists across the company to measure impact, validate hypotheses, and advance state-of-the-art AI capabilities through rigorous experimentation. This is a unique opportunity to build systems at scale while deepening your expertise in distributed systems, service reliability, and experimentation methodologies. You will thrive in this role if you enjoy solving complex distributed systems challenges, learning experimentation fundamentals, and building reliable infrastructure that accelerates Microsoft’s progress in AI.
Job Responsibility:
Design, implement, and maintain clean, reliable, testable code using best practices and responsible AI-assisted development while escalating blockers early
Use AI tools responsibly across the SDLC, reviewing and validating AI-generated changes to ensure correctness and maintainability
Work with partner engineering teams, PMs, and experts (privacy, security, SRE) to understand requirements, apply customer feedback/telemetry, and deliver scalable, reliable, user-centric features
Build extensible, maintainable services and features with strong diagnosability, reliability, and production-readiness
Participate in on-call rotations, troubleshoot live-site issues using least-privileged access, and improve TSGs, telemetry, and fixes that reduce future incidents
Contribute to engineering and operational excellence through automation, tooling, documentation, and process improvements
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 are required for this role
These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter
Nice to have:
Master's Degree in Computer Science or related technical field AND 3+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 5+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
Experience working with cloud platforms (Azure, AWS, GCP), building and maintaining distributed systems including deployment, monitoring and troubleshooting of production workloads
Experience using observability tools (logging, metrics, tracing) to diagnose service issues and improve system reliability
Experience with experimentation platforms, A/B testing at scale, and statistical methodologies for measuring product impact and driving data-informed ship decisions
Familiarity with AI-assisted development workflows or responsible use of AI coding tools