Architect, prototype, and lead the iteration on AI agent experiences that reimagine domain-specific workflows across Copilot in Office and Copilot Cowork, rapidly validating feasibility, UX, and technical approaches while pushing the frontier of agent-driven productivity. Drive the delivery of features by operating at the true intersection of SWE, applied science, product, and domain expertise, where a single AI engineer can unlock disproportionate impact by translating customer needs, domain knowledge, model capability, and product intent into intelligent, production-ready systems. Design evaluation frameworks and observability tools to monitor real-time agent health, investigate customer feedback, and build continuous learning systems for end-to-end AI workflows. Invent and lead industry-defining domain-specialized agent experiences by working directly with customers and domain experts to understand complex and long-tail workflows, explore new interaction paradigms, and build robust system architectures that enable natural collaboration between humans and AI. Cultivate a culture of technical excellence and continuous learning. Proactively identify and drive systemic improvements to agent development platforms, engineering and domain knowledge bases, build processes, and engineering standards, while mentoring coworkers to elevate the technical bar of the team. Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python Bachelor's or Master's degree in Computer Science, Engineering, or related technical field AND 4+ years technical engineering experience (or Ph.D. and 3+ years). 4+ years of professional software development experience with coding in languages including, but not limited to, Python, Typescript/Javascript, C, C++, or C 2+ years of experience training, fine-tuning, and evaluating ML/LLM models, including data preparation, experiment design, offline/online validation, and performance optimization. 2+ years of production experience architecting and deploying applications with LLMs and/or agent systems. Course work, research, or relevant training in ML/AI/LLMs, with a demonstrated track record of pushing into new interdisciplinary areas at the intersection of applied science, engineering, and product. Proven track record of technical leadership, including orchestrating complex agentic systems in production, advanced prompt design, tool/function calling, context and memory management, routing/planning, and evaluation. Deep understanding of async programming patterns, microservices architecture, and event-driven systems. Prior experience in a professional domain such as finance, accounting, or human resources, with an understanding of domain-specific workflows, business rules, and customer needs. Experience in forward-deployed engineering or similar customer-facing technical roles, partnering directly with customers to build secure and scalable systems, operate deployed solutions, and continuously improve them based on production feedback. Growth mindset, resilience, and communication & collaboration skills.