New 
Senior Software Development Engineer - Gen AI Infrastructure and Solutions
 Microsoft | |
 United States, Washington, Redmond | |
 Oct 14, 2025 | |
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OverviewThe Gen AI Infrastructure and Solutions team is building large-scale GenAI training infrastructure, LLM-based solutions and tools. We provide the infrastructure for teams in CoreAI and other Microsoft Groups to fine-tune LLMs for their own scenarios. We also build services and solutions of SLMs and LLMs for 1P&3P on Azure, like Azure Machine Translation service. As a Senior Software Development Engineer - Gen AI Infrastructure and Solutions, you will work on the infrastructure and tools to support large scale model fine-tuning, and evaluation. You will also work on the service to host SLMs/LLMs for translation to process trillions of characters per month. Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.
ResponsibilitiesAs a team member of our team, you will participate in developing innovative solutions across AI Platform. Responsibilities include the following. Collaborate with senior engineers and researchers to build and optimize training infrastructure and tools for LLMs, SLMs, multimodal, and code-specific models. Design and implement new AI features for Azure Machine translation and Language services. Design, build and improve the services with high scalability and reliability. Contribute to the deployment and monitoring of services in production environments. participate in the efforts to deliver and improve engineering systems and practices to ensure service quality in complex cloud environments. | |