Android Software Engineer

About ActAI

There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal prompting.

Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. We believe products will greatly reduce hallucinations

Our objective is to organise anyone's life, allowing us all to spend time on valuable and meaningful things.

Role

As 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.