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# Android Engineer (C++)

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[Apply for this job](#job-application)[View company](https://jobicy.com/company/binance.md)ShareRemote from[APAC](https://jobicy.com/job-region/apac.md)SalaryUndisclosedDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceOpen levelPublished1 Oct 2026Apply before31 Oct 2026Listing views21Application actions2Application toolkit

## Make your next move.

Prepare your resume, explore your fit, and draft a cover letter for this opportunity.

AI Summary

## The role, at a glance.

Binance is seeking a senior Android-focused C++ engineer to build shared, high-performance mobile capabilities across Android and iOS. The role covers Chromium-based browser-kernel features, an OpenGL ES mobile game engine, native graphics, and cross-platform C++ infrastructure. A major focus is integrating and optimizing on-device AI, including LLM inference, agents, quantization, and performance trade-offs on resource-constrained devices. The engineer will collaborate across mobile, graphics, AI, and platform teams while ensuring robust testing, stability, responsiveness, and maintainability.

## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

5/5EasyHard

### Pace & Pressure

4/5RelaxedFast-paced

### Autonomy Level

4/5GuidedFull ownership

### Communication Load

4/5IndependentCollaborative

AI insightThis is a highly specialized senior engineering role requiring deep C++ and native mobile systems knowledge across Android, iOS, graphics, Linux, networking, and browser-engine domains. It also requires practical expertise in edge AI deployment and optimization, where latency, memory, power, and accuracy must be carefully balanced.

## Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate$170,000US market range$145k–$210k0$231k

AI insightNo salary is disclosed in the posting, so these are estimated annual US-market base-salary figures in USD for a senior/principal-level mobile systems engineer with 8+ years of C++, Android/iOS, graphics, and on-device AI expertise. Actual pay may differ materially by work location, level, and total-compensation structure.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[C++](https://jobicy.com/jobs?search_keywords=C%2B%2B.md)[Android](https://jobicy.com/jobs?search_keywords=Android.md)[iOS](https://jobicy.com/jobs?search_keywords=iOS.md)[Cross-platform mobile development](https://jobicy.com/jobs?search_keywords=Cross-platform%20mobile%20development.md)[OpenGL ES](https://jobicy.com/jobs?search_keywords=OpenGL%20ES.md)[Chromium](https://jobicy.com/jobs?search_keywords=Chromium.md)[On-device AI](https://jobicy.com/jobs?search_keywords=On-device%20AI.md)[LLM inference](https://jobicy.com/jobs?search_keywords=LLM%20inference.md)[Performance optimization](https://jobicy.com/jobs?search_keywords=Performance%20optimization.md)[Linux and POSIX](https://jobicy.com/jobs?search_keywords=Linux%20and%20POSIX.md)

Sample interview questionsHow would you design a shared C++ feature that must run efficiently on both Android and iOS?I would isolate platform-independent business and performance-critical logic in a portable C++ core, then expose narrow platform adapters for lifecycle, rendering, storage, networking, and UI integration. I would define clear ownership and threading contracts, use automated unit tests for the shared core, and validate behavior with platform-specific integration tests and profiling.

How do you approach optimizing an on-device LLM for a mobile application?

I first establish target latency, memory, battery, accuracy, and device-coverage requirements. I then profile model loading, token generation, CPU/GPU utilization, and memory allocations; evaluate quantization and runtime options; optimize context and KV-cache handling; and benchmark representative workloads across target devices before making quality-performance trade-offs.

What factors would you investigate when an Android graphics feature has intermittent frame drops?

I would inspect frame timing, render-thread scheduling, SurfaceFlinger composition behavior, GPU and CPU utilization, shader and texture costs, synchronization points, allocation churn, and thermal throttling. I would use Android tracing and graphics profiling tools to identify whether the bottleneck is application rendering, composition, memory bandwidth, or scheduling, then verify improvements under realistic workloads.

How would you troubleshoot a native C++ crash that occurs only on iOS or only on Android?

I would collect symbolicated crash reports, compare platform-specific compiler settings and ABI assumptions, inspect threading and object-lifetime behavior, and reproduce with sanitizers where possible. I would also review platform adapter code, JNI or Objective-C++ boundaries, alignment and memory-management assumptions, and any differences in graphics or network callbacks.

How do you ensure third-party AI SDKs or APIs do not compromise mobile application reliability?

I would evaluate the SDK's runtime footprint, privacy model, licensing, update cadence, failure modes, and device compatibility before integration. I would wrap it behind an internal interface, add timeouts and fallbacks, protect calls with robust error handling and telemetry, pin and test supported versions, and validate performance and battery impact across representative devices.

Opportunity details

## About this role.

### Responsibilities

* Design and implement cross-platform mobile features for both Android and iOS using modern C++.
* Design and implement new features for our in-house mobile browser kernel based on Chromium, with a focus on Android and iOS.
* Design and implement new features for our in-house mobile game engine based on OpenGL ES and native graphics technologies.
* Explore and integrate AI capabilities into mobile applications, including on-device AI inference, LLMs, intelligent agents, and AI-powered user experiences.
* Design and optimize AI-related components for mobile and edge devices, with a focus on inference latency, memory usage, CPU/GPU utilization, power efficiency, and overall user experience.
* Collaborate with cross-functional teams to define, design, and deliver new features across Android, iOS, and shared C++ infrastructure.
* Effectively integrate and utilize third-party data sources, AI services, SDKs, and APIs.
* Write and execute unit tests to ensure code robustness, including edge cases, usability, and overall reliability.
* Troubleshoot issues, fix bugs, and continuously improve application performance, stability, and responsiveness.
* Balance high responsiveness, stability, efficiency, maintainability, and user experience when designing and implementing mobile systems.

### Requirements

*  8+ years of solid software development experience, with significant experience in mobile or cross-platform development.
* Strong C++ development experience, with solid knowledge of C++14 and above.
* Solid understanding of cross-platform mobile development and the ability to work effectively across both Android and iOS.
* Familiarity with Android internals, including SurfaceFlinger and the Android graphics/rendering pipeline, with the ability to read and understand relevant source code.
* Familiarity with iOS system architecture and native development concepts.
* Strong understanding of Linux memory management and experience with POSIX APIs.
* Good knowledge of computer networks and experience developing cross-platform applications using C++.
* Good understanding of OpenGL/OpenGL ES principles and mobile graphics rendering.
* Basic knowledge of ARM architecture and assembly is preferred.
* Solid understanding of modern AI architectures, especially the Transformer architecture and core concepts such as attention mechanisms.
* Familiarity with LLMs, AI agents, agentic workflows, and common AI application architectures.
* Familiarity with on-device AI / edge AI, including model deployment, inference, quantization, and performance optimization on mobile devices.
* Understanding of the trade-offs between model size, inference latency, memory consumption, power consumption, and accuracy on resource-constrained devices.
* Bachelor’s/Master’s degree in Computer Science, Engineering, or a related field, or equivalent industry experience.
* Good understanding of the mobile technology landscape, architectures, trends, and emerging technologies.

### Preferred Qualifications

* Experience developing shared C++ infrastructure or libraries used across Android and iOS.
* Experience with AI model deployment or inference optimization on Android, iOS, or other edge devices.
* Experience with model quantization, pruning, KV cache optimization, or other techniques for improving on-device AI performance.
* Familiarity with AI inference frameworks or runtimes such as llama.cpp, ONNX Runtime, TensorFlow Lite, Core ML, or similar technologies.
* Experience integrating LLMs or AI agents into mobile applications.
* Familiarity with multimodal AI, speech AI, or other on-device AI technologies is a plus.
* Experience contributing to popular mobile libraries or maintaining a widely used open-source project.
* Knowledge of Android and iOS performance analysis and optimization techniques.
* Strong problem-solving skills and the ability to work effectively across C++, Android, iOS, graphics, browser engines, JavaScript engines, and AI technologies.

### Compensation

### Additional Information

Show more

[Apply now >](https://jobicy.com/jobs/154324-android-engineer-c.md)

>  Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md)

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