Android Software Engineer

CompanyA1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows.

Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior.

RoleAs an Android Software Engineer, you own the Android client experience, how AI feels, behaves, and performs on mobile devices. This is not a thin client role. You will build a production Android application where AI interactions are core to the product, and performance, reliability, and clarity matter.

Focus

• 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.

Ideal Experiences

• 3+ years of Android development experience using Kotlin.
• Hands-on experience integrating AI features (e.g. LLM, vision, speech APIs).
• Strong understanding of asynchronous programming (Coroutines, Flow).
• Familiarity with REST or gRPC APIs and structured data formats.
• Strong debugging and performance profiling skills.
• Comfort building in environments with latency, partial failure, and non-deterministic behavior.
• Experience with MLKit or light on-device inference.
• Published production apps on the Google Play Store.

Outcomes

• Stable, smooth, and reliable real-world use android applications.
• Performance is optimized: responsive, low-latency, and efficient on memory and CPU.
• Production issues are detected early, monitored effectively, and resolved with clear root-cause analysis.

Tech Stack

• Kotlin / Java
• SQL / noSQL
• TensorFlow Lite (on-device inference)