• Implementing Observability Frameworks: Building the tools and templates that provide visibility into model performance, data drift, and training statistics, ensuring our continuous retraining loops are robust. • Engineering for Efficiency: Developing systems to track and optimize compute costs and training performance, allowing us to scale our ML efforts sustainably. • Building Experimentation Tooling: Executing on the roadmap for internal tools that enable Data Scientists and ML Engineers to iterate and deploy experiments with minimal friction. • Developing SaaS-grade ML Services: Writing high-quality, maintainable Python code to build and automate services that sit at the core of our ML lifecycle. • Bridge-Building: Working alongside our Staff Engineer to implement architectural designs and collaborating with SRE/DevXP teams to ensure our solutions are production-ready and easily managed.

• Exhibit mastery of the ‘In-Store’ team’s domain, taking a leading role in the design and architecture of complex systems and influencing technical direction and strategy. • Own the delivery of large-scale features and projects, coordinating efforts across multiple teams and ensuring alignment with overall business objectives. • Provide mentorship and technical leadership to both junior and senior engineers, helping to grow the technical expertise within the team and fostering a culture of continuous improvement. • Collaborate closely with Product, Design, and other stakeholders to shape requirements, making architectural and technical decisions that balance quality, performance, and delivery timelines. • Ensure the implementation of high-quality, resilient, and scalable distributed systems, incorporating resilience mechanisms and best practices. • Lead troubleshooting and incident management efforts, taking a proactive role in resolving critical production issues and improving system reliability. • Advocate for and implements improvements in development practices, such as enhancing CI/CD processes, optimising infrastructure as code, and increasing test automation coverage. • Coordinate and lead cross-team technical initiatives, ensuring consistency and integration between various services and platforms. • Stay ahead of emerging technologies and trends, assessing new tools and techniques to enhance the team's capabilities. • Demonstrate ownership of the team's delivery pipeline, ensuring that code quality, testing standards, and deployment practices are continuously optimised.

• Integrating state of the art learning science into our product to enable learners and teachers to quickly identify and address learning gaps on the fly. • Partnering with public school districts with a high percentage of Free and Reduced Price Lunch students to build and scale our teacher and learner tools to millions of learners who otherwise would not have discovered us. • Building tools for teachers to use Khan Academy as a strategic supplement in their classrooms. • Harnessing the power of AI to deliver the product capabilities where applicable • Collaborating with cross-functional teams to deliver high-quality software and solutions.

• Lead and scale a high-impact trajectory planning team. • Drive commercial launch readiness for trajectory planning. • Apply a rigorous, metrics-driven framework to quantify and improve on-road performance. • Manage the computational efficiency and real-time performance of trajectory generation algorithms. • Lead the rapid triage and root-cause analysis (RCA) of critical fleet incidents. • Oversee the successful execution of complex, multi-team initiatives. • Coordinate with peer leads to provide technical leadership. • Define and negotiate quarterly and annual technical roadmaps aligned with company-level autonomy milestones.