Software Engineer II - Android Applications in Gurgaon, भारत

Job Description :Roles & Responsibilities :- Design and ship high-quality Android applications for consumer and enterprise audiences, while leveraging AI/LLM tools to build intelligent product features and accelerate development workflows.- Build and maintain robust Android applications using Kotlin, Jetpack Compose, and XML layouts.- Own end-to-end feature delivery - from architecture and UI to API integration, testing, and release.- Integrate cloud LLM APIs (OpenAI, Anthropic, Gemini, etc.) into mobile apps to power intelligent, user-facing features.- Build internal AI-powered developer tools - code assistants, smart documentation helpers, automated testing aids, and similar workflow accelerators.- Design lightweight prompt engineering solutions and manage LLM API call lifecycles - error handling, retries, latency, and cost-awareness on the client side.- Collaborate with backend, QA, design, and product teams in a structured enterprise environment.- Contribute to reusable internal components or SDKs that make LLM capabilities easier to leverage across the https://jobeax.com/link/xc1EXVDC5gJW2kqU Profile :- 4 - 6 years of professional Android development with a portfolio of shipped consumer and/or enterprise applications.- Hands-on experience integrating at least one AI-powered feature or developer tool into a real product or workflow.- Strong understanding of Android performance, debugging, and release processes in a structured team environment.- Practical knowledge of LLM concepts - prompts, context engineering, basic RAG, knowledge bases, and latency/cost tradeoffs.- Familiarity with MCP and how it enables LLM-connected workflows.- CI/CD experience, automated testing (unit + instrumentation), and comfort with enterprise-grade release https://jobeax.com/link/Kbe5qpShWPdEUqGH Required :- Android Developer role demands strong mobile engineering as the foundation, augmented with practical AI/LLM integration experience - Kotlin (must-have) : coroutines, flows, modern async patterns- Jetpack Compose + XML layouts - hands-on with both- Android architecture : MVVM, clean architecture, Jetpack components (ViewModel, StateFlow, Navigation, Room, WorkManager)- Dependency injection - Hilt or Koin- LLM API integration : calling and consuming OpenAI, Anthropic, Gemini or equivalent in production- Prompt engineering basics : context management, token usage, cost tradeoffs- RAG (Retrieval-Augmented Generation) : working knowledge of retrieval pipelines and when to apply them- Knowledge base construction : familiarity with chunking, embedding, and indexing content for LLM consumption- MCP (Model Context Protocol) - basic awareness of how tools, APIs, and data sources connect to LLM workflows (ref:hirist.tech)