Principal Software Engineering Manager

Business Group Overview  

Within AI Platform, the Azure AI Search team powers rich knowledge base experiences for apps of all kinds. We integrate the best of Microsoft AI for content understanding, search relevance, and knowledge sources.  

Job Purpose Overview  

As a Principal Software Engineering Manager, you will shape end-to-end customer and developer experiences for Azure AI Search—ensuring customers can discover, adopt, and succeed with AI capabilities at global scale. You will operate where product experience meets cloud services, setting direction that improves reliability, security, and time-to-value. 

You will lead and grow a high-performing team that discovers, defines, and delivers new product capabilities—often turning ambiguous customer needs into clear, shippable features and reliable components. You will foster a high-trust environment where engineers collaborate, move quickly, and continuously raise the bar in a demanding and exciting space. You will also apply evolving AI tools and AI-assisted engineering practices to design, implement, test, and ship AI features faster and more safely across UX flows, portal experiences, samples, SDKs, and APIs. 

You will thrive in a highly dynamic environment by staying close to users—listening, learning, and translating feedback into product and experience improvements. You will own key entry points and integration experiences (including partner integrations) so customers can onboard smoothly, extend the product confidently, and realize value quickly. 

You will set technical direction and drive operational excellence from design through production—building for security, reliability, and observability, and ensuring features can be operated with confidence at scale. You’ll establish strong engineering systems (quality, incident readiness, and release practices) and use data from real-world usage to continuously refine the product experience. 

Success in this role is measured by outcomes customers feel: simpler onboarding, clearer and more consistent experiences across every surface area, and secure, reliable features that run smoothly in production—enabling faster adoption of new AI capabilities. Success is also reflected in the team you build: a high-trust, high-performance culture that adapt

• Leads the disciplined adoption and continuous improvement of AI tools and Responsible AI practices across the SDLC, ensuring accountability for AI-generated assets and using engineering health metrics to drive measurable process improvements and share learnings. 

• Leads engineering excellence for production services by driving diagnosability and incident prevention (debugging, telemetry, retrospectives), strengthening secure and privacy-preserving operations (least privilege), and raising code quality through timely, high-signal reviews, automated analysis, and best practices (including GenAI) to deliver secure, maintainable, high-performing code while proactively managing blockers and risks. 

• Managers deliver success through empowerment and accountability by modeling, coaching, and caring. Model: Live our culture. Embody our values. Practice our leadership principles. Coach: Define team objectives and outcomes. Enable success across boundaries. Help the team adapt and learn. Care: Attract and retain great people. Know each individual’s capabilities and aspirations. Invest in the growth of others. 

• Leads cross-group planning and execution (project/release/work management) by breaking long-term vision into milestones, driving estimation and capacity planning, and ensuring secure, compliant delivery with operational readiness (flighting, rollback, and disaster recovery). 

• Partners with internal and external stakeholders to validate user requirements and feasibility, incorporates customer insights and success metrics (including accessibility/globalization), and advocates for customer security and privacy needs across the solution. 

Minimum Qualifications 

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. 

Preferred Qualifications 

• Master's Degree in Computer Science or related technical field AND 8+ years technical engineering exper