• Designing - gathering all required specifications and finding an appropriate solution. • Implementing the software running on the hosts in our data centers. • Implementing unit tests. • Researching, proposing, and integrating relevant open-source projects based on product objectives. • Improving internal processes and systems on a consistent basis.

• Design, evolve, and maintain core libraries, framework extensions, and shared components used across all engineering teams • Take ownership of system performance, scalability, and high-load architecture, ensuring core services can handle massive throughput with low latency • Proactively monitor production behavior, investigate complex application/database performance bottlenecks, and introduce advanced metrics, dashboards, and alerting systems • Establish and advocate for best practices in concurrency, memory management, and resource utilization across the backend ecosystem • Collaborate with cross-functional teams including backend, web, mobile, QA, and product teams • Take ownership of specific functional areas within our large-scale architecture • Leverage AI tools and assistants as integral parts of your development workflow—from system design to code review • Contribute to maintaining high test coverage, predictable production behavior, and seamless scalability • Drive engineering excellence through modern practices and continuous improvement

• Lead backend development within your squad: technical guidance, code review culture, and mentoring of fellow engineers • Own services end-to-end — from requirements and system design through production deployment and operation • Guide complex, multi-quarter features through the full delivery lifecycle • Work closely with backend, frontend, QA, and product teams to ensure seamless delivery • Mentor engineers on architecture, best practices, and production troubleshooting • Shape system designs and contribute to the technical roadmap

• Own backend features for AI-powered educator tools: architecture, implementation, deployment, observability. • Design and build data ingestion and transformation pipelines. • Build and evolve APIs that serve learning insights and AI-generated content. • Integrate LLM capabilities into the product. • Use agentic coding tools as part of your daily workflow. • Write specs, ADRs, and context docs. • Ship features with Flutter engineers, PM, and designer. • Find ways to automate repetitive engineering work with AI.