• Build and evolve mobile instrumentation SDKs for iOS (Swift / Obj-C) and Android (Kotlin / Java), prioritizing performance, stability, and a great developer experience. • Design and ship SDK features such as session tracking, crash reporting, sampling strategies, automatic context propagation, and OpenTelemetry integrations. • Own projects end-to-end. • Break large, ambiguous problems into incremental deliverables: design modular solutions, ship MVPs, gather feedback, iterate quickly. • Ensure quality: automated tests, CI, documentation, and smooth, backwards-compatible upgrade paths. • Collaborate cross-functionally with backend, frontend, product, and solutions engineering to ensure cohesive end-to-end observability workflows. • Engage with the open-source community: review PRs, discuss design proposals, and help guide external contributors. • Mentor teammates, participate in technical design discussions and help shape the mobile observability roadmap.

• Be part of an agile, cross functional team; • Work closely with the all development teams responsible for the mobile applications and their backend; • Be proactive, hands on, involved in tasks and related communication; • Participate and lead the design, development, maintenance, and every part of the delivery process of our Android apps; • Help drive the technical competency in the Android engineering area; • Have shared ownership of our product vision.

• Work with a fast-growing team to build and scale impactful products • Build smooth, stable, and elegant Android applications using Kotlin and modern Android APIs • Own features end to end, from inception and design through implementation and launch • Collaborate cross-functionally with Product Designers, Product Managers, Backend Engineers, and Data teams • Work with Kotlin, Android SDK, Jetpack Compose, MVVM, Coroutines & Flow (preferred) or RxJava, and Retrofit & Room

• Build and maintain production Android apps using Kotlin. • Integrate AI-powered features (chat, vision, voice, recommendations) via backend APIs. • Design UX patterns for AI interactions, including streaming responses, retries, and partial results. • Optimize performance, memory usage, and responsiveness for AI-heavy flows. • Implement analytics, logging, and feedback capture to support AI evaluation and iteration. • Collaborate closely with backend and ML engineers on API contracts and system behavior. • Ensure app stability, security, and scalability in production environments.