Principal Software Engineer

Build the platform that makes every engineering team more effective! Set technical direction. Define and drive a platform roadmap that connects long-term architectural investments with the most important needs of engineering teams and the business. Apply AI to meaningful engineering problems. Develop AI-assisted and agent-based capabilities for workflows such as troubleshooting, testing, migrations, and operational analysis. Establish evaluations and safeguards that make their results trustworthy. Treat the platform as a product. Work directly with partner teams to understand friction, validate solutions, and turn repeated challenges into self-service capabilities that engineers choose to adopt. Make safe delivery easier. Build automated validation, progressive rollout, observability, and recovery mechanisms that help teams move quickly without transferring unnecessary risk to production. Own outcomes end to end. Lead initiatives from problem definition and architecture through implementation, adoption, and ongoing operation. Measure success through developer experience, reliability, performance, and cost. Lead across organizational boundaries. Align stakeholders on priorities and technical tradeoffs, resolve ambiguous problems, and build shared approaches that enable teams to evolve independently. Raise the engineering bar. Stay close to code, mentor engineers, guide design reviews, and foster a culture of curiosity, accountability, and continuous improvement. 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 These requirements include but are not limited to the following specialized security screenings: Experience designing, building, and operating distributed systems or shared platform services in production.

building platforms or developer tools adopted across multiple teams, with demonstrated improvements in engineering productivity, service reliability, or operational efficiency.

designing interfaces and workflows that support both human developers and AI agents, with clear contracts, discoverable capabilities, and auditable execution.

using telemetry, profiling, and production investigations to identify systemic bottlenecks and deliver measurable performance or cost improvements.

modernizing established systems through incremental architecture changes and migrations that preserve customer and partner confidence.

Ability to translate ambiguous requirements and developer needs into practical, maintainable technical solutions.