The Microsoft Store team is focused on ensuring that Windows users can easily discover and engage with the experiences they need, and that Independent Software Vendors (ISVs) are motivated to build Windows experiences. The role aims to contribute to the development and maintenance of the Windows client application and related components, delivering a performant and fluid experience for millions of users worldwide.
Requirements
- Proven experience coding in languages including, but not limited to, C, C++, C-Sharp, Java, JavaScript, or Python
- Experience in application development for Windows or other platforms.
- Experience with conversational memory systems and agentic AI concepts.
- Familiarity with at least one AI orchestration framework (e.g., LangChain, Semantic Kernel, MCP).
- Experience integrating AI models into applications via APIs or SDKs.
- Experience with LLM-based agent systems or recommendation systems (retrieval, ranking, personalization).
- Solid analytical skills and ability to interpret experiment results.
Responsibilities
- Partner closely with project management, applied science, data, and design teams to define opportunities where artificial intelligence (AI) and large language models (LLMs) can improve user experience.
- Participate in experiment design and execution to evaluate model performance, feature impact, and customer satisfaction.
- Break down complex initiatives into actionable engineering tasks with realistic delivery estimates.
- Implement, test, and optimize features, ensuring low latency and high performance in AI-driven scenarios.
- Stay current with advancements in LLM capabilities, retrieval/ranking systems, and recommendation models—and proactively identify where they can be applied.
- Communicate complex technical and experimental findings clearly to both technical and non-technical stakeholders.
- Ensure AI and data usage complies with responsible AI and privacy principles.
Other
- 3 days / week in-office
- Travel 0-25 %
- Collaborating across design, program management, and data disciplines.
- Thrive on solving complex and ambiguous challenges.
- Collaborating with experienced engineers, applied scientists, and data experts
