Software Engineer II
About The Position
Microsoft's Substrate is a massively scaled service underpinning Microsoft 365 offerings for more than a billion users worldwide. The Observability Intelligent Cloud group is building data processing and analytics services to support AI, monitoring, alerting, analytics, automation, and related scenarios, with a focus on low cost and end-to-end data governance across the data lifecycle. The Software Engineer II contributes to the development and evolution of this AI-powered data platform. Working with senior and principal engineers and partner teams, this engineer implements, tests, deploys, and maintains well-scoped components of large-scale data platform services. The work includes service infrastructure, data processing, analytics, and AI- and LLM-enabled experiences, while following Microsoft's privacy, responsible AI, security, and compliance standards. The role offers opportunities to deepen technical expertise in data processing and service engineering.
Requirements
- Bachelor's degree in Computer Science or a related technical field and at least 2 years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
- Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
Nice To Haves
- Master's degree in Computer Science or a related technical field and at least 3 years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python; or bachelor's degree in a related field and at least 5 years of such experience; or equivalent experience.
- Experience designing, building, testing, and operating cloud services, distributed systems, data pipelines, telemetry processing, or large-scale data systems.
- Experience with AI, machine learning, LLM-based workflows, data analytics, service intelligence, automation, time-series data, or production engineering systems.
- Experience applying quality engineering practices such as unit testing, integration testing, code reviews, observability, secure coding, and operational readiness.
- Problem-solving skills and the ability to learn quickly, communicate clearly, and collaborate effectively across teams.
- Demonstrated ability to deliver well-scoped feature work and contribute to small- to medium-sized projects.
Responsibilities
- Contribute to development and evolution of the AI-powered data platform and deliver well-defined features with senior engineers, principal engineers, and partner teams.
- Build and improve data platform infrastructure, including frameworks, pipelines, service components, APIs, and automation using artificial intelligence.
- Develop scalable, high-performance software components for large datasets, targeting low latency and high availability under senior technical guidance.
- Contribute to AI- and LLM-enabled experiences that help teams understand production signals, analyze service data, improve engineering productivity, and make data-driven operational decisions.
- Develop reliable, maintainable, and well-tested software for data processing, analytics, workflow automation, and intelligent service operations.
- Apply Microsoft's data privacy, responsible AI, security, and compliance standards in engineering work.
- Implement, test, deploy, and maintain well-scoped components for data platform infrastructure, frameworks, pipelines, APIs, analytics, and automation.
- Work with senior engineers on service components that process large-scale service data, telemetry, metadata, configuration, and workflow outputs used by AI/ML and LLM-enabled platform experiences.
- Contribute to AI-powered engineering and operations capabilities, including data processing, signal analysis, intelligent summarization, workflow automation, service insights, and evidence generation.
- Collaborate with engineers within and outside the team to integrate assigned components into larger OIC and Substrate systems, following established design patterns and engineering standards.
- Participate in design discussions for assigned features by evaluating options, documenting assumptions, asking questions, and incorporating feedback from senior technical owners.
- Participate in code reviews as both reviewer and reviewee to improve quality, reliability, maintainability, and engineering practices.
- Improve platform quality and live-site readiness through tests, monitoring, dashboards, diagnostics, documentation, and fixes for recurring operational issues.
- Develop technical depth in assigned features while learning AI-assisted engineering, data processing, service reliability, privacy, compliance, and responsible AI practices.
- Embody Microsoft's Culture and Values.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
