Android Software Engineer

Android Software Engineer

London

Full time, Hybrid

The Company

There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native. The mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows with minimal prompting.

The 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 behaviour. The objective is to help users enjoy completing daily tasks in over 90% reduced time.

The 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.

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.

Requirements

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)

The Team

The best products today in the world were built by small, world class teams. You will be joining a high talent density and hands-on team who make decisions collectively, move at rapid speed, striking a balance between shipping high-quality work and learning. Joining the team requires the ability to bring structure, exercise judgment, and execute independently. The collective goal is to give users a truly magical product.