• Own backend features end-to-end: discovery, design, implementation, rollout, and long-term reliability/operations • Design and evolve distributed systems (services, pipelines, data stores) with strong performance, scalability, and resiliency • Build and maintain APIs (REST/GraphQL, where relevant) and data access patterns supporting analytics and search use cases • Establish strong engineering fundamentals: code reviews, testing strategies, incident readiness, and operational excellence • Apply an experimentation-first approach: define hypotheses, define success metrics/guardrails, run controlled rollouts and A/B tests when appropriate, and write clear readouts for stakeholders. • Bring evaluation discipline to AI-assisted work: treat prompts/configs like versioned artifacts, design regression tests, measure quality changes, and monitor for drift (the same way you would for performance or correctness) • Use GenAI productively and responsibly (for coding assistance, debugging, and design reviews), while maintaining high standards for correctness, security, and privacy. • Mentor teammates and raise the bar through documentation, pairing, and lightweight coaching on best practices