Principal Software Engineer-M365 Copilot

Serve as a technical leader and domain expert for shipping AI- and ML-based intelligent services and products, staying ahead of industry trends and applying them to influence product and platform direction. Lead architectural design for complex backend, data, and ML systems that meet security, compliance, scalability, and reliability requirements, and translate vision into actionable milestones, estimates, and plans. Define and drive engineering quality strategy - establishing metrics, standard practices, and reusable design patterns that raise reliability, maintainability, and developer efficiency across the team. Partner with stakeholders and cross-functional teams - including product managers, applied scientists, and data engineers - to align on requirements, incorporate feedback, and deliver high-impact features and platform improvements. Lead the creation and improvement of internal tools and frameworks that accelerate developer velocity, automation, and overall system

effectiveness. Mentor and grow engineers through code reviews, design reviews, and technical guidance, raising the bar for engineering excellence across the team. Embody our culture and values. Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. These requirements include but are not limited to the following specialized security screenings: 6+ years experience designing, implementing, and operating large-scale, distributed backend, data-intensive, or ML-driven and evaluation systems in production. Demonstrated ability to set technical direction, influence architecture, and mentor engineers to deliver measurable impact in fast-paced and ambiguous environments. Proven ability to drive cross-team engineering initiatives, balancing hands-on contributions with strategic technical leadership. 5+ years’ experience developing and deploying AI/ML or GenAI products or systems at multiple points in the product cycle from ideation to shipping. Experience architecting and operating large-scale distributed systems, data platforms, or ML pipelines in production. Experience working with SOTA AI tooling to accelerate software development lifecycle. Experience with Azure platforms and modern deployment practices such as CI/CD, containerization, and microservices. Experience defining and tracking engineering metrics such as performance, reliability, and observability, and mentoring engineers to raise technical quality. A growth mindset, passion for continuous learning, and drive to make both systems and teams more efficient and effective.