Software Engineer II

Core AI is at the forefront of Microsoft’s mission to redefine how software is built and experienced. We are responsible for building the foundational platforms, services, programming models, and developer experiences that power the next generation of applications using Generative AI. Our work enables developers and enterprises to harness the full potential of AI to create intelligent, adaptive, and transformative software.  

The Future of Scalable Software Engineering (FoSSE) team’s objective is to build capabilities to enable AI-enabled modernization of very large code bases on a large scale and with very high quality. 

Job Purpose Overview 

In this role, you will help define the future of software development. You will help build and combine static analysis and ML tools to help AI handle the scale of large code bases. You will work with state-of-the-art LLMs and reasoning models, very large code bases, and use data from pull requests, static analysis warnings reports, and developer feedback from AI recommendations to build AI agents that scale. 

You will grow by developing both static analysis and ML based techniques that are needed to build coding agents that scale to large code bases. 

You will be onsite 3 days a week and learn and grow through working with talented colleagues. 

Standard Company, Culture, Candidate Value Proposition – Use the following: 

Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we’re dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world. 

Coding 

Creates and implements code for a product, service, or feature, reusing code as applicable. Writes and learns to create code that is extensible and maintainable. Considers diagnosability, reliability, and maintainability with few defects, and understands when the code is ready to be shared and delivered. Applies coding patterns and best practices to write code. 

Machine Learning  

Knowledge and implementation of an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. 

Algorithm Design and Implementation 

The ability to design, analyze, implement, optimize, profile and experimentally evaluate computer algorithms. Includes knowledge of practical applications of algorithms in software engineering.