Job Summary
We're seeking an experienced Android Engineer to build and maintain large-scale, multi-module Android applications with expertise in complex build systems and AI integration. You'll design scalable Gradle architectures, optimize build performance, and develop high-performance Jetpack Compose UIs. You'll implement robust Firebase Crash Reporting, diagnose memory and ANR issues, and apply strong dependency injection patterns using Hilt/Dagger to ensure scalable, testable solutions across feature teams. Core Technical Requirements In addition to advanced Android development skills, you should have hands-on experience integrating LLM APIs and working with MCP (Model Context Protocol) frameworks in production environments. You should understand token management, context handling, agentic workflows, multi-agent orchestration, and AI error recovery strategies. You should also demonstrate expertise in at least 2-3 of the following: • Kotlin Coroutines & Flow • Data Store and Room • OkHttp and Protocol Buffers • Work Manager Experience with memory profiling, Firebase crash analysis, performance optimization, and large-scale modular applications is essential. What We're Looking For We value candidates with an active GitHub portfolio featuring multiple Android projects that showcase strong architecture and scalability. Additional strengths include open-source contributions, technical writing, and experience shipping AI-powered features. Experience with LLM platforms such as Claude, OpenAI, or MCP tool servers is highly desirable. Most importantly, you're able to balance architectural thinking with practical delivery, navigating complex modular systems while remaining focused on real-world mobile constraints.
Key Responsibilities
We're seeking an experienced Android Engineer to build and maintain large-scale, multi-module Android applications with expertise in complex build systems and AI integration. You'll design scalable Gradle architectures, optimize build performance, and develop high-performance Jetpack Compose UIs. You'll implement robust Firebase Crash Reporting, diagnose memory and ANR issues, and apply strong dependency injection patterns using Hilt/Dagger to ensure scalable, testable solutions across feature teams. Core Technical Requirements In addition to advanced Android development skills, you should have hands-on experience integrating LLM APIs and working with MCP (Model Context Protocol) frameworks in production environments. You should understand token management, context handling, agentic workflows, multi-agent orchestration, and AI error recovery strategies. You should also demonstrate expertise in at least 2-3 of the following: • Kotlin Coroutines & Flow • Data Store and Room • OkHttp and Protocol Buffers • Work Manager Experience with memory profiling, Firebase crash analysis, performance optimization, and large-scale modular applications is essential. What We're Looking For We value candidates with an active GitHub portfolio featuring multiple Android projects that showcase strong architecture and scalability. Additional strengths include open-source contributions, technical writing, and experience shipping AI-powered features. Experience with LLM platforms such as Claude, OpenAI, or MCP tool servers is highly desirable. Most importantly, you're able to balance architectural thinking with practical delivery, navigating complex modular systems while remaining focused on real-world mobile constraints. We need 6+ years of exp.