Mobile Software Developer

DataOrbis; Piet Retief; On-site; ZAR 900,000 - 1,400,000; Full time

Job summary

Smollan Technologies is seeking a Senior Mobile Developer to own the mobile codebase, capture pipeline, offline sync, and release path. You will push performance on limited hardware and drive on-device AI model integration.

The role emphasizes Flutter across platforms, with deep Android/Kotlin experience, native interop, and a mindset for low-latency, energy-efficient mobile computing.

Qualifications

• Experience delivering cross-platform mobile apps with Flutter.
• Proficiency in native Android development using Kotlin.

Responsibilities

• Build and optimise high-performance capture pipelines on the Flutter camera stack.
• Design offline-first local persistence models with resilient uploads.
• Integrate TensorFlow Lite models on-device using Dart and native delegates.
• Maintain Flutter and Android-native code with modular architecture.
• Manage automated CI/CD pipelines and telemetry.
• Collaborate with back-end and ML teams; field test with users.

Skills

Flutter

Kotlin

Dart

Edge AI

Mobile architecture

Cross-platform

Tools

CameraX

Camera2

TensorFlow Lite

CI/CD

ProGuard

Job description

At Smollan Technologies, we provide a unified, technology-driven suite of products that redefines how businesses handle data. We don't just build apps; we turn on-device capture into the sensing front end of an applied AI system. Our Engineering team is no different. We are moving away from traditional CRUD clients over REST APIs and flipping the switch on next-gen, edge-computed mobile solutions. By deploying continuous camera pipelines and on-device inference to a managed field fleet under hostile network conditions, we are transforming mobile software into an intelligent, real-time strategic asset.

Our vision for our Senior Mobile Developer is to take complete end-to-end ownership of our mobile application codebase, capture pipeline, offline synchronisation, and release path. This isn't just about rendering UI screens; it's about deep-diving into native platform interop, squeezing maximum performance out of lower-specification hardware, and driving continuous AI model integration right on the device. The ideal candidate is a forward-thinking mobile engineer who is not only fluent in cross-platform Flutter architecture, but actively excited about native Android depth (Kotlin), edge inference, and pushing on-device computer vision limits.

We believe that when you hire unique, creative problem solvers and give them flexibility and independence, incredible things happen. Our culture is rooted in a foundation of trust. We foster a diverse, inclusive environment where our people are genuinely cared for, inspired, and empowered to thrive. We are looking for dreamers who love a challenge and want the autonomy to solve it.

What You Will Do

• Camera & Capture Pipeline Engineering: Build and optimise high-performance capture pipelines on the Flutter camera stack (CameraX/Camera2 interop), implementing real-time on-device quality gating (blur, glare, exposure) and deterministic metadata tracking.
• Offline-First Architecture & Sync: Design durable local persistence models using outbox patterns and resilient background queues, ensuring resumable, idempotent uploads across severe network disconnections and process restarts.
• On-Device AI & Edge Inference: Integrate lightweight TensorFlow Lite/LiteRT models directly onto devices using Dart bindings and native delegates, balancing real-time frame rates against thermal and battery limits.
• Architecture & Codebase Ownership: Maintain the core Flutter (Dart) and Android-native (Kotlin) codebase using feature-first modularisation, clean boundaries, and strict unidirectional data flow.
• Release Pipeline & Telemetry: Manage automated CI/CD pipelines, ProGuard obfuscation, App Bundle splits, staged enterprise rollouts via Managed Google Play/EMM, and proactive telemetry tracking.
• Cross-Functional Collaboration: Co-own versioned API schema contracts with back-end engineers, partner with machine learning teams on vision models, and jump into direct field testing with end users.