Android Software Engineer

TECHKNOWLEDGEY PTE. LTD.; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

TECHKNOWLEDGEY PTE. LTD. in Singapore is seeking an experienced Android Software Engineer to own the Android client experience for an AI-powered product.

You will build a production Android application where AI interactions are core, focusing on reliability, performance, and clear user experiences. Responsibilities include developing with Kotlin, integrating AI features via backend APIs, designing UX for streaming responses, and ensuring stability across devices.

Qualifications

• 3+ years of Android development experience using Kotlin.
• Hands-on experience integrating AI features (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.

Responsibilities

• Build and maintain production Android apps using Kotlin.
• Integrate AI-powered features 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.

Skills

Android development with Kotlin

Asynchronous programming (Coroutines/2

REST or gRPC APIs

Performance profiling

MLKit / on-device inference

Tools

TensorFlow Lite

Android Studio

REST APIs

gRPC

Job description

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

Their 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.

Overview:

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.

Tech Stack

• Kotlin / Java

• SQL / noSQL

• TensorFlow Lite (on-device inference)