Principal Software Engineer

Quick Facts

• Role: Principal Software Engineer (hands-on technical leader)

• Focus: Distributed platform engineering and AI-enabled automation

Description

Lead the technical direction and delivery of a platform that makes engineering teams more effective by simplifying infrastructure into intuitive capabilities. Apply AI-assisted and agent-based capabilities to workflows such as troubleshooting, testing, migrations, and operational analysis, with trustworthy evaluations and safeguards. Own initiatives end to end—from architecture and implementation through adoption and ongoing operation—across scalability, performance, observability, and developer experience.

Responsibilities

• Set technical direction and drive a platform roadmap linking architecture investments to team and business needs.

• Develop AI-assisted and agent-based workflow capabilities with evaluation, safeguards, and human oversight.

• Treat the platform as a product by partnering with teams to remove friction and build self-service capabilities.

• Make safe delivery easier with automated validation, progressive rollout, observability, and recovery mechanisms.

• Lead outcomes end to end, measuring success via developer experience, reliability, performance, and cost.

• Lead across organizational boundaries to align stakeholders and resolve ambiguous problems.

• Raise the engineering bar by mentoring, guiding design reviews, and fostering continuous improvement.

Requirements

• Meet security screening requirements and pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

• Bachelor’s Degree in Computer Science or related field AND 6+ years engineering experience with coding in languages including C, C++, C#, Java, JavaScript, or Python (or equivalent experience).

• Experience designing, building, and operating distributed systems or shared platform services in production.

• Experience building platforms or developer tools adopted across multiple teams with measurable improvements.

• Hands-on experience integrating large language models or agents into engineering workflows, including tool integration, evaluation, permission boundaries, and human oversight.

• Experience designing interfaces and workflows for both human developers and AI agents with clear contracts and auditable execution.

• Depth in platform domains such as service frameworks, data infrastructure, observability, CI/CD, experimentation, configuration management, or cloud infrastructure.

• Experience using telemetry, profiling, and production investigations to identify bottlenecks and improve performance/cost.

• Ability to modernize systems via incremental architecture changes and migrations that preserve confidence.

• Track record balancing exploration with pragmatic delivery and successful prototype-to-production adoption.

• Solid systems engineering fundamentals (API design, concurrency, data management, failure handling, performance analysis).

• AI-forward mindset with ability to identify valuable AI use cases, implement safely, and evaluate correctness, security, reliability, and cost.

• Demonstrated technical leadership across multiple teams, including architectural decisions and production adoption.

• Ability to translate ambiguous requirements into maintainable technical solutions.

• Strong communication and collaboration skills for influencing decisions and mentoring engineers.

Benefits

• Certain roles may be eligible for benefits and other compensation.