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We are the Copilot and Agents Core Platform team. We are building a scalable platform to develop and run copilot workloads that bring intelligent agents into the daily workflow of millions of Microsoft 365 users. The
extensible runtime infrastructure we build enables rapid experimentation, safe deployment, and seamless
orchestration of LLM-powered agents. Our mission is to empower developers to build, compose, and
operate AI agents with agility and confidence. We operate at the cutting edge building AI workflows for productivity including long-running tasks and proactive workflows and permanent compute and memory.
We are seeking a highly experienced and technically visionary Principal Software Engineering Manager to lead the architecture and development of the next-generation agent runtime platform and features. This role is pivotal in shaping the future of agent-based computing at Microsoft, enabling the runtime for long running tasks, extensibility at scale and supporting multi-agent collaboration.
The engineering manger leads disciplined use of artificial intelligence (AI) tools across the software development lifecycle (SDLC), integrating Responsible AI practices and recommending improvements. Guides collaboration with stakeholders to confirm user requirements and leverages feedback channels for design improvements. Owns and leads architecture discussions, manages design documents, evaluates new technologies, and reviews complex designs. Guides teams in creating test strategies, incorporating security testing, and leveraging AI tools for test automation. Leads managing dependencies and collaborates across teams to align schedules and resolve conflicts. Guides development process, ensuring extensible, maintainable, and secure code using best practices. Acts as an expert in troubleshooting, applying least-access principles, and conducting incident retrospectives. Leads code reviews, ensuring adherence to best practices. Drives project planning, anticipates future goals, and ensures compliance with security requirements. Guides experimentation, deployment, live site maintenance, and incident response, ensuring safe and efficient operations. Integrates telemetry to monitor system behavior and improves designs based on analysis. Guides development tool selection and continuous integration in production. Ensures compliance with security and regulatory standards, mentors on learning and development, and advocates for best practices and security-informed engineering. In addition, this role has people management responsibilities including driving employee growth and development, executing projects, and managing performance.
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.
Lead the team that architects and evolves the core runtime infrastructure to support systems for agentic memory and conversation storage and the agent runtime platform components for M365 Copilot Chat.
Drive AI-native engineering: Champion responsible use of AI across the SDLC, improve team productivity with AI tools, and ensure accountability for AI-generated artifacts.
Raise engineering quality and reliability: Lead code reviews, debugging, incident retrospectives, telemetry practices, and continuous improvements in code quality, testability, security, and maintainability.
Own architecture and cross-team design: Guide complex system design, evaluate technology choices, manage dependencies, and ensure solutions meet scalability, reliability, performance, cost, and compliance requirements.
Lead delivery, live-site health, and people growth: Drive project execution, safe deployments, observability, incident response, customer-focused decision making, and team success through coaching, empowerment, and accountability.
Required Qualifications:
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications:
#CAP #Copilot
Software Engineering M5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
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Microsoft builds Windows, Azure, Office and the Copilot family of AI assistants, and operates one of the largest AI training and inference fleets in the world. Microsoft Research and the AI platform teams work across foundation models, systems for large-scale training, and applied ML in every product line.
Founded in 1975 and headquartered in Redmond, Washington, the company is also OpenAI's principal compute partner and ships AI tooling for developers through GitHub, VS Code and Azure AI.
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