Job Code: DTDLPL-56136

Gurgaon, Haryana, India

Expires on 29/09/2026

Required Experience

2 - 4 Years

Skills

Android,

Kotlin,

Dagger

Job Description

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 workplace.
- Contribute to reusable internal components or SDKs that make LLM capabilities easier to leverage across the team.

Skills 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

Ideal Profile:

- 3–5 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 processes.

📌 AI FullStack Engineer (India)
🏢 Deutsche Telekom Digital Labs
📍 India