OverviewThe Microsoft Content team powers AI-driven experiences for more than 1B users across Copilot, Bing, Edge, Windows, and Xbox. We are seeking a Principal Software Engineer to define and lead the technical direction for the next generation of intelligent, large-scale content platforms.
In this role you will be responsible for shaping multi-year technical strategy, driving architectural coherence across organizations, and building systems that serve as foundational platforms for multiple product surfaces.
You will lead the design and evolution of distributed backend systems, cloud-native infrastructure, and data platforms that operate at global scale with strict requirements for availability, latency, security, and cost efficiency. These systems form the backbone for intelligent user experiences and must be designed for long-term extensibility and operational excellence.
Building on this foundation, you will guide the integration of LLM-powered capabilities into production systems-defining patterns for retrieval, orchestration, evaluation, and responsible AI. You will ensure these capabilities are not isolated features, but deeply embedded, reliable, and scalable parts of the platform.
This role requires exceptional technical judgment, the ability to operate in highly ambiguous spaces, and a track record of influencing across teams and organizations. You will work closely with engineering leaders, product leaders, and applied scientists to align technical investments with long-term business outcomes.
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- Technical Strategy & Architecture Leadership
- Define and drive long-term technical strategy for large-scale distributed systems and platforms spanning multiple teams and organizations.
- Establish architectural principles, patterns, and standards that ensure consistency, scalability, and maintainability across services.
- Lead the design of system-of-systems architectures, integrating services, data, and AI capabilities into cohesive platforms.
- Make high-impact technical decisions that balance innovation, risk, cost, and long-term sustainability.
- Platform & Systems Ownership
- Architect and evolve backend services, APIs, data infrastructure, and platform capabilities that operate at global scale.
- Ensure systems meet stringent requirements for availability, latency, throughput, security, privacy, and cost efficiency.
- Drive operational excellence through observability, resiliency design, incident management, and continuous improvement.
- Identify and eliminate systemic inefficiencies across services, infrastructure, and development workflows.
- AI Systems Integration & Evolution
- Define how LLMs and intelligent systems are integrated into core platform architecture (not as isolated features).
- Establish patterns for retrieval, grounding, orchestration, memory, and tool use in production systems.
- Lead the design of evaluation frameworks for quality, safety, latency, reliability, and business impact.
- Ensure responsible AI practices, including safety, privacy, and governance, are embedded into system design.
- Cross-Org Influence & Execution
- Influence technical direction across teams, organizations, and partner groups without direct authority.
- Drive alignment between engineering, product, and applied science on platform strategy and execution.
- Lead complex, multi-team initiatives from concept through delivery, ensuring clarity, momentum, and results.
- Represent technical strategy and progress to senior leadership.
- Engineering Excellence & Talent Development
- Raise the engineering bar across the organization through design reviews, technical mentorship, and standards setting.
- Act as a role model for deep technical rigor, high-quality execution, and end-to-end ownership.
- Mentor senior engineers and emerging leaders, helping grow the next generation of technical talent.
- Foster a culture of innovation, accountability, and continuous improvement.
QualificationsRequired Qualifications:- Bachelor'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 equivalent experience.
Preferred Qualifications:- Master'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 Bachelor's Degree in Computer Science or related technical field AND 15+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR equivalent experience.
- Proven track record of architecting and delivering large-scale distributed systems or platforms used by millions of users.
- Deep expertise in backend systems, cloud-native architecture, and service-oriented or microservices-based design.
- Experience owning and evolving production systems with high availability, low latency, and solid operational rigor.
- Solid fundamentals in system design, distributed systems, data modeling, and performance optimization.
- Demonstrated ability to drive technical strategy and influence across multiple teams or organizations.
- Experience leading complex, ambiguous, and high-impact technical initiatives end-to-end.
- Experience designing and scaling LLM-powered applications, AI agents, or intelligent platforms in production.
- Deep expertise in prompt orchestration, retrieval systems, agent workflows, and tool integration.
- Experience building evaluation and experimentation frameworks for AI systems (quality, safety, latency, business impact).
- Proven ability to integrate AI capabilities into large-scale platforms in a reliable, secure, and cost-efficient manner.
- Experience with responsible AI practices, governance, and safety systems.
- Track record of defining industry-leading technical approaches or influencing platform-level direction.
#MicrosoftAI
Software Engineering IC6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 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 $220,800 - $331,200 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.
