Android Developer

ELLIOTT MOSS CONSULTING PTE. LTD.; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading tech consulting firm in Singapore seeks a Senior Android Developer to lead end-to-end development of Android applications. The ideal candidate will have significant experience in Kotlin and Java, a track record of delivering production-level apps, and a strong understanding of AI/ML. This role involves collaboration with UX and backend teams to create secure and scalable mobile solutions, while ensuring high quality and optimal performance on various devices.

Qualifications

• 7+ years software engineering experience.
• 5–6 years Android development experience using Kotlin and Java.
• Strong experience delivering production-level apps.
• Proficient with Android SDK and Jetpack components.
• Solid CS fundamentals including data structures and algorithms.

Responsibilities

• Lead end-to-end development of Android applications.
• Work closely with UX, backend, and AI/data teams.
• Integrate AI-driven features and external APIs.
• Ensure performance and reliability across devices.
• Contribute to CI/CD and DevOps processes.

Skills

Kotlin

Android Development

AI/ML Fundamentals

Java

Git

Agile Tools

Debugging Skills

Leadership/Mentoring

Tools

Android Studio

Gradle

GitHub Actions

Jenkins

Fastlane

Job description

Job Description

We are looking for a highly experienced Senior Android Developer with strong hands‑on expertise in building modern, scalable, and user‑centric Android applications. The ideal candidate must have deep Android development skills, strong fundamentals in AI/ML, and experience working with cloud platforms to support AI‑driven use cases and next‑generation mobile solutions.

You will be responsible for end‑to‑end Android app development — from architecture and design to deployment and performance optimization — while collaborating with cross‑functional teams to deliver secure, high‑quality, and innovative mobile experiences.

Key Responsibilities

• Lead end‑to‑end development of Android applications using Kotlin, Jetpack Compose, and modern Android architecture.
• Work closely with UX, backend, cloud, and AI/data teams to build scalable and intuitive mobile solutions.
• Support and integrate AI‑driven features, including workflow automation, cloud AI services, or on‑device intelligence.
• Integrate REST/GraphQL APIs, WebSockets, and third‑party SDKs with strong offline handling and caching.
• Ensure performance, reliability, and responsiveness across diverse Android devices, including foldables.
• Implement secure coding practices (OAuth2, MFA, AES/RSA, certificate pinning, TLS/SSL, OWASP).
• Contribute to DevOps pipelines and CI/CD using GitHub Actions, Jenkins, Fastlane, and automated testing tools.
• Perform code reviews, mentor developers, and adhere to clean architecture principles.
• Continuously optimize performance (memory, network, battery, UI rendering).
• Explore and adopt emerging technologies such as Kotlin Multiplatform, AI cloud services, and new Compose capabilities.

Basic Qualifications

• 7+ years of software engineering experience.
• 5–6 years of Android development using Kotlin and Java.
• Strong experience delivering production‑level apps (Play Store or enterprise).
• Proficiency with Android SDK, Jetpack components, Material Design, and architectural best practices.
• Solid CS fundamentals: data structures, algorithms, design patterns.
• Experience with Git, CI/CD, Agile tools (Jira, Confluence).
• Good understanding of AI/ML fundamentals.
• 3+ years of hands‑on experience in AI/ML projects (GenAI/Agentic AI is a strong plus).
• Strong communication, debugging, analytical, and leadership/mentoring skills.

Technical Skill Sets

• Languages & Tools: Kotlin, Java, Python, Android Studio, Gradle, Git.
• Frameworks: Jetpack Compose, ViewModel, Flow, LiveData, Room, DataStore, WorkManager, Hilt/Dagger.
• Architecture: MVVM, MVI, Clean Architecture, modular/multi‑module apps.
• Networking: Retrofit, OkHttp, GraphQL, WebSockets.
• AI & Cloud:Good understanding of AI concepts and cloud AI integrationsExposure to Google Gemini API / AWS Bedrock / Vertex AIOptional: ML Kit, TFLite
• Firebase & Cloud Integration: Crashlytics, Analytics, FCM; AWS/GCP services (Lambda, S3, Cloud Run, API Gateway).
• Testing & DevOps: JUnit, Espresso, Mockito; Fastlane, GitHub Actions, Jenkins; SonarQube.
• Security: Android Keystore, AES/RSA, OAuth2, certificate pinning, TLS/SSL, OWASP Mobile Security standards.
• Good to Have: Kotlin Multiplatform, Flutter/React Native, IoT, AR/VR, feature flagging tools.