Top Tech Jobs & Startup Jobs in Mumbai

Design and deliver pixel‑perfect mobile interfaces for iOS and Android across financial products. Create wireframes, flows, prototypes and production-ready UI, build and maintain design systems, collaborate with engineers, and iterate based on analytics and user feedback to ensure usability, accessibility and platform consistency.

Build and maintain production Android applications with AI-native interactions. Integrate chat, vision, voice, and recommendation features through backend APIs; design resilient streaming and partial-result experiences; optimize performance, memory, and responsiveness; and implement analytics, logging, monitoring, security, and feedback systems. Collaborate with backend and ML engineers on API contracts, diagnose production issues, and deliver stable, scalable mobile experiences.

Build and maintain production-grade iOS applications using Swift and SwiftUI, integrating AI features through backend APIs. Design reliable AI interaction patterns, optimize performance, memory, battery, and latency, and support on-device inference. Collaborate with backend and ML engineers on APIs and system behavior, capture user feedback for AI evaluation, maintain App Store quality, and diagnose production issues through monitoring and root-cause analysis.

Define the AI-native phone’s hardware platform strategy, roadmap, and specifications. Evaluate mobile SoCs and components, including CPU, GPU, NPU, memory, connectivity, power, thermal, and battery capabilities. Translate product and AI requirements into hardware decisions, assess platform customization needs, collaborate with ODMs, OEMs, and chipset vendors, review architecture proposals, and establish validation criteria for current and future on-device AI workloads.

Evaluate, benchmark, deploy, and optimize AI models for on-device execution on Android hardware. Responsibilities include integrating models into applications and system services, reducing latency, memory use, and power consumption, applying quantization and compression, leveraging CPU, GPU, and NPU acceleration, and building hybrid local/cloud inference routing with agent systems.

Define the product vision and user experience for an AI-native phone. Identify high-value workflows, design proactive interactions across the operating system and applications, translate concepts into engineering requirements, prioritize prototype and launch capabilities, evaluate technical feasibility with Android and AI teams, and validate interaction patterns through user research.

Integrate AOSP or custom ROMs with smartphone hardware, including BSPs, vendor HALs, firmware, drivers, boot processes, cameras, sensors, modems, Wi-Fi, and Bluetooth. Troubleshoot hardware and firmware compatibility, collaborate with OEMs, ODMs, and chipset vendors, and optimize device power consumption and performance.

Build agent capabilities for AI phones, including workflow orchestration, tool integrations, context retrieval, memory, multi-step execution, long-running stateful workflows, and reliability improvements. Integrate local and cloud model providers, develop evaluation and regression tests, and support production AI infrastructure. The role requires backend or AI application engineering expertise, programming proficiency, LLM API and tool-calling experience, and knowledge of APIs, distributed systems, state management, and asynchronous execution.

Build integrations between AI agents and first-party applications, exposing structured actions and information retrieval interfaces. Develop cross-application workflows, reusable SDKs, and reliable asynchronous APIs supporting search, creation, updates, sending, and deletion. Manage authentication, authorization, and permissions; investigate integration limitations; and collaborate with Android engineers on system-level application access.

Develop and modify Android system services, privileged APIs, and AI integration interfaces at the OS level. Build reliable agent-to-system execution capabilities, manage permissions, IPC, application lifecycle, and background execution, and optimize system performance and resource consumption. Collaborate with AI agent engineers while debugging and improving Android platform functionality.