Senior Applied AI Engineer

The Business & Industry Copilots (BIC) group is a rapidly growing organization that is responsible for the Microsoft Dynamics 365 suite of products, Microsoft Copilot Studio, Power Apps, Power Automate, Dataverse, AI Builder, Microsoft Industry Solution and more. Microsoft is considered one of the leaders in Software as a Service in the world of business applications and this organization is at the heart of how business applications are designed and delivered. 

The BIC Agent Cloud organization at Microsoft is among the most thrilling to be a part of. BIC Agent Cloud products herald a new era of business applications that are data-initiated, AI-driven, built for collaboration, and simplify business problem-solving with low-code/no-code platforms. Our team is responsible for developing the platform for Dynamics 365 suite of business applications, and the Power Platform suite of low-code tools. We are at the vanguard of digital transformation, enabling organizations to revolutionize the creation of Copilots through state-of-the-art AI solutions and product offerings. This new productivity era leverages the power of data, AI, and productivity tools to deliver unmatched experiences across all channels. 

We are seeking a highly accomplished Senior Applied AI Engineer with deep expertise in large language models (LLMs) - including both text and multimodal systems - reinforcement learning, agentic AI architectures, and large-scale model training and inference optimization. This is a senior role for an individual contributor who brings together cutting-edge research excellence and strong applied instincts. You will operate at the frontier of AI science and product innovation, driving the design and deployment of next-generation AI systems at scale. You will need to design and build systems that allow LLMs to reason over large amounts of data as well as leveraging lighter weight models in place for specific scenarios for specific scenarios. We are looking for an individual capable of working with research teams and partnering with them to deliver joint solutions.  This can range from working together on building fine-tuned models to coming up with ways to build custom LLMs for specific product needs. 

We are excited to hear from candidates who are passionate about making a significant impact on how people interact with their computers, and who are excited about the opportunity to be at the forefront of growing new business for Microsoft. This is a rare chance to be part of a cutting-edge technology that is poised to revolutionize productivity and innovation.  

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile  commute of a non-U.S., country-specific location are expected to work from  the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.   

Responsibilities

• Design and develop advanced AI models and agentic systems for real-world applications. 

• Own and drive end-to-end model training, including data pipeline design, distributed training optimization, and performance evaluation. 

• Stay up to date with the latest advancements in LLM, NLP, deep learning, search and AI research.  

• Research and develop an understanding of the state-of-the-art tools, technologies, and methods being used in the research community and product groups.  Stay current with the latest research, technologies, and best practices in AI/ML, and Translate research breakthroughs into production-ready algorithms, contributing to core capabilities such as search, planning, and long-term memory. 

• Collaborate closely with engineering, product, and research teams to productionize models, build scalable, robust pipelines and provide support for in production AI Models/Agents 

• Collaborate with stakeholders to define project goals, success criteria, and deliverables.  Deliver end-to-end lifecycle of machine learning models, from prototyping and implementation to evaluation, deployment, and monitoring.