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Microsoft is leading the AI transformation, and agents are at the center of this shift. As organizations build thousands of agentic solutions that act autonomously, coordinate with humans, and power every business process, Microsoft Copilot Studio is becoming the platform to create and manage trusted, reliable, and enterprise‑ready agents. The Copilot Studio AI Foundations team is at the forefront of AI Agility and builds the platforms and services enabling teams across Microsoft to ship AI with speed and confidence. We design and operate the systems that underpin evaluations at scale, define the AI development process, and provide the metrics and gates that ensure every change is validated with high quality insights. Our work enables rapid experimentation, fast deployment of model updates, and ultimately higher AI quality and stronger customer usage across Microsoft. We are hiring a Principal Software Engineer to lead architecture and hands on development of the platforms that make this possible. You will collaborate with applied science and product partners to build reliable, high performance systems that power experimentation, evaluation, and AI readiness at scale. Your work will help teams ship AI features faster, safer, and more frequently while driving measurable improvements in quality and customer satisfaction.
Job Responsibility:
Set technical strategy for large scale, AI first services aligned to customer outcomes and adoption
Lead architecture and design for complex systems
validate options with specs, prototypes, and data
Write secure, performant, well tested code and raise standards through thoughtful reviews
Collaborate with Applied Science and AI experts to design, build, and ship cutting edge generative AI features that redefine AI first SaaS
Improve resiliency, security, reliability, latency, and cost using strong observability and operational practices
act as DRI for key services and drive durable fixes
Unblock cross team dependencies, manage risks, and land integrated, production ready solutions at scale while mentoring engineers and sharing best practices
Requirements:
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
6+ years of software development experience in application or services development on cloud-based platforms or AI-driven systems
1+ years of experience working with Large Language Models (LLMs) and Generative AI
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
Nice to have:
Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
Ability to lead technical strategy across ambiguous AI problem spaces and influence multi team engineering decisions
Expertise building or operating large scale platforms and systems that support AI quality, safety, reliability, or experimentation with strong observability, diagnosability, and operational excellence for AI driven workloads
Experience with distributed systems architecture, multi tenant cloud services, and high availability backend engineering
Proven track record mentoring senior engineers and raising the technical bar through design leadership, reviews, and hands on guidance
Ability to navigate ambiguity, deliver in an agile environment, adopt new technologies, and collaborate effectively across teams