Principal Software Engineering Manager, Responsible AI Services

Quick Facts

• Role: Principal Software Engineering Manager
• Focus: Customer-facing Responsible AI services with scalable, high-availability cloud architecture

Description

Lead a team of software engineers to build customer-facing Responsible AI services with high performance, low latency, and high availability. Own the end-to-end development lifecycle and production readiness of the services the team builds, ensuring systems meet business requirements and service KPIs. Collaborate with engineers, scientists, and product managers to deliver Responsible AI capabilities across text, image, audio, video, and multimodal content.

Responsibilities

• Lead a team of software engineers, including hiring, growing, and upskilling talent
• Review design and code artifacts for large-scale distributed cloud services with a focus on availability, scalability, robustness, and observability
• Drive project development across the organization and work with subject matter experts and stakeholders to deliver development and release plans
• Ensure team-owned systems meet business requirements and service KPIs
• Take end-to-end responsibility for development lifecycle and production readiness; drive the team’s DevOps culture
• Promote modern software engineering best practices through code and design reviews; make service decisions using data and telemetry
• Collaborate with stakeholders to deliver cohesive, end-to-end experiences for customers
• Embrace a growth mindset and stay current with state-of-the-art technologies to improve customer experience

Requirements

• Bachelor’s degree in Computer Science or related technical field AND 6+ years of technical engineering experience coding in C, C++, C#, Java, JavaScript, Python (or equivalent)
• Ability to pass required security screenings (including the Microsoft Cloud background check upon hire/transfer and every two years thereafter)
• 5+ years directly managing software engineers
• 5+ years designing and delivering highly available, large-scale cloud services and distributed systems
• 4+ years designing and delivering machine learning model infrastructure, hosting, and operations
• Ability to influence and inspire peers across engineering and product development
• Depth of knowledge of software architecture, design tradeoffs, and mature DevOps practices

Benefits

• Competitive base pay range (varies by location)
• Eligibility for benefits and other compensation

Opportunity to collaborate hands-on with the team on technical artifacts and leadership/team process.