Role Overview :

We are seeking an Android Developer with 14 years of experience who is excited about integrating Generative AI and LLM-powered capabilities into mobile applications.

The ideal candidate should have strong Android development skills, a good understanding of AI/ML concepts, and a passion for building innovative user experiences powered by modern AI technologies.

Key Responsibilities :

- Design, develop, test, and maintain high-performance Android applications using Kotlin and Java.

- Integrate LLMs and Generative AI capabilities into Android applications through APIs and SDKs.

- Develop AI-powered features such as chat interfaces, content generation, summarization, recommendation engines, and intelligent assistants.

- Collaborate with Product, Design, Data Science, and Engineering teams to define and implement innovative solutions.

- Optimize application performance, scalability, and security.

- Work with RESTful APIs, cloud services, and backend systems.

- Monitor, troubleshoot, and resolve application issues.

- Stay updated with emerging trends in Android development, Generative AI, and LLM ecosystems.

Required Skills & Qualifications :

- Bachelor's degree in Computer Science, Engineering, Information Technology, or related field.

- 2-6 years of hands-on experience in Android application development.

- Strong proficiency in Kotlin and Android SDK.

- Experience with Android Jetpack components, MVVM architecture, and modern Android development practices.

- Good understanding of REST APIs and JSON-based integrations.

- Experience working with Git and CI/CD pipelines.

- Understanding of Large Language Models (LLMs) and Generative AI concepts.

- Exposure to AI platforms such as OpenAI, Gemini, Claude, Llama, or similar models.

- Knowledge of prompt engineering and AI application workflows.

- Familiarity with Firebase, cloud platforms, and analytics tools.

Preferred Qualifications :

- Experience integrating AI/LLM APIs into mobile applications.

- Exposure to Retrieval-Augmented Generation (RAG) architectures.

- Understanding of vector databases and semantic search concepts.

- Experience with on-device AI models and AI inference optimization.

- Knowledge of Python, backend development, or AI frameworks is a plus.

- Contributions to personal AI projects, hackathons, or open-source initiatives.