Available for new opportunities · India/Remote

Nimish Nandwana

Lead Mobile Engineer

9 years building mobile products that reach millions of people. Native Android, Flutter, and Kotlin Multiplatform — with an eye on performance, architecture, and AI-augmented workflows.

10M+ users

5 markets

25+ apps released to stores

View Resume Get in touch

About

I've spent the better part of a decade making software that fits in people's pockets. What keeps me in mobile engineering isn't the platforms - it's the discipline. A 16ms frame budget doesn't negotiate. A crash rate above 0.5% shows up in your store rating within a week. You learn to care about precision fast.

Currently at Deutsche Telekom Digital Labs I lead a team shipping a streaming platform to 10M+ users across Europe. Most of my work these days sits at the intersection of architecture, performance, and team process - making sure a system that started as one app can scale to three without accumulating the kind of technical debt that kills velocity two years later.

Outside of my day job I build things that scratch my own itches. PaisaTracker is a self-hosted finance agent that reads my transaction emails, structures them with an LLM, and pings me on Telegram to categorize the transaction and sends me a daily and monthly summary of the spends. The LIC Agent Toolkit came from watching insurance agents struggle with a portal that looks like it was designed as a deterrent. Building for yourself is how you stay honest about what "good" actually means.

I'm also genuinely excited about where AI tooling is going for software teams. I wrote the AGENTS.md rules and Cursor project configuration that now govern code review across all our apps - not as a replacement for human judgment, but as a way to catch the boring mistakes before they reach a reviewer. I think that's the right use of the technology: raising the floor, not replacing the craft.

Stack

What I reach for, and why

Android

KotlinJavaJetpack ComposeMVVM / MVIHiltWorkManagerRoomCoroutinesFlowMaterial 3

Flutter & Cross-platform

FlutterDartBLoCRiverpodPlatform channelsKMPKtorSQLDelightCompose Multiplatform

Performance & Native

JNI / NDKC++Baseline profilesR8 / ProGuardLeakCanaryPerfettoSystrace

Quality & Security

TDDJUnit5MockitoEspressoOAuth2 / SAMLBiometric authCertificate pinningPCI DSS

AI Tooling

CursorClaude APIAGENTS.mdProject rulesOpenClawDeepSeekAWS BedrockMCP integrations

Platform & DevOps

FirebasePlay ConsoleFastlaneGitLab CIGitHub ActionsHetzner VPSCloudflare

Experience

Deutsche Telekom is a leading global integrated telecommunications company headquartered in Bonn, Germany. It is Europe's largest telecommunications provider by revenue and operates worldwide (notably through its T-Mobile subsidiary in the US and various European markets).

Lead Mobile Developer

Gurgaon

Lead an 8-engineer mobile org delivering an Android-first streaming platform at 10M+ MAU across 5 European markets.

Reduced cold launch from 3.2s to 1.8s (~44%) via baseline profiles, lazy initialization, and JNI hot-path optimization
Brought crash rate from 1.8% to 0.3% — sustaining 99.7% crash-free sessions and a 4.8/5 store rating
Designed and rolled out an AI-assisted code review pipeline (Cursor + AGENTS.md) that catches architectural drift before PRs reach human review
Built a shared component for keyboard navigation that handles accessibility compliance across Compose and legacy View hierarchies — currently used in 3 flagship apps
Drove KMP adoption for shared domain and networking modules, eliminating duplicated business logic across apps
Own the mobile roadmap and experimentation pipeline — 50+ A/B tests per quarter informing release decisions
I run the sprint cadence end-to-end: daily standup, sprint planning, scope changes, retrospectives, and Play Console release.
New modules are built in Jetpack Compose, while existing ones are migrated incrementally based on priority and team capacity.
Built structured rule sets for AI tooling (AGENTS.md, Cursor rules) encoding business logic, module relationships, and constraint boundaries - so Cursor/Claude understands impact scope before suggesting changes reducing hallucination risk and improving AI-assisted code quality across the codebase.

KotlinJetpack ComposeFlutterHiltCoroutinesJNI/NDKAGENTS.mdLLM

Grappus Technologies is an Indian design and development studio that builds digital experiences, mobile applications, websites with a strong focus on UI and animation and brand identities.

Senior Mobile Developer

Gurgaon

Tech lead on 10+ enterprise Android engagements spanning fintech, productivity, and internal tooling.

Modularized monolithic codebases into 50+ feature modules - 70% build time reduction via parallel compilation
Delivered PCI DSS payment flows, biometric auth, certificate pinning, and OAuth2/SAML SSO with zero security audit findings across four fintech clients
Introduced Jetpack Compose and Coroutines on newly created modules while keeping RxJava on legacy paths — incremental migration without big-bang rewrites
Built offline-first sync (WorkManager + Room) with conflict resolution for high-traffic collaboration apps at 99.9% data integrity
Implemented i18n for 30+ locales including Arabic RTL and CJK — sustained 60fps on entry-tier hardware

KotlinJetpack ComposeWorkManagerRoomOAuth2PCI DSSRxJava

SimplylocalX is a dual-purpose product developed by Wabi Tech that serves both as an AI-powered neighborhood social network and an enterprise digital signage platform. By combining these two facets, the product bridges the gap between hyper-local community engagement and physical business display management.

Android Developer

New Delhi

Built geospatial and IoT Android applications with a focus on performance and device connectivity.

Built a shared UI component library deployed across 5 enterprise Android applications
Engineered a JNI bridge to a C++ map rendering engine — ~50% memory reduction on low-end devices
Delivered the BLE communication layer for IoT device connectivity and real-time data streaming
Implemented offline-first sync via WorkManager with background reconciliation

KotlinJavaJNIC++BLEWorkManager

Projects

Professional work and personal experiments

A personal finance automation pipeline, self-hosted on Hetzner

Anuradha is an AI agent that watches my Gmail and parses incoming transaction emails. It asks me to categorize each one on Telegram, sends a reminder at 10 PM for anything uncategorized, and delivers a daily and monthly spend summary every morning at 6 AM. No third-party finance APIs.

IMAP IDLE for real-time email processing - no polling
LLM-based parsing that distinguishes transaction emails from marketing
Remembers category preference per payee - needs less input over time

PythonOpenClawDeepSeek APIIMAP IDLESQLiteTelegram BotHetzner

Cross-platform Flutter app for warehouse operations

End-to-end Flutter delivery for a cross-platform warehouse operations app targeting Android and iOS. Owned architecture, API contracts, and store-ready builds.

Wired native auth, analytics, and deep links through platform channels
Dart-side business logic kept fully unit-testable
Widget and golden test patterns plus Fastlane CI for gated releases

FlutterDartBLoCPlatform channelsFastlaneFirebase

RAG-powered knowledge engine for business documents

Paperlink AI turns business documents - PDFs, policies, contracts - into an intelligent chat assistant that answers customer questions instantly. Built on a RAG pipeline, it indexes uploaded documents and serves structured, accurate answers through an embeddable widget. The goal is reducing bounce rates and support load by giving visitors clear answers instead of making them dig through long documents.

RAG-powered engine that indexes documents and retrieves context-aware answers
Embeddable chat widget - deployable on any website in minutes
Handles poorly formatted or complex documents and returns structured responses

RAGAIDocument IntelligenceEmbeddingsChat WidgetSaaS

AI Workflow

How I use AI tooling in practice

AGENTS.md & Cursor project rules

At DT Digital Labs I authored the project rules and AGENTS.md files that now govern AI-assisted code review across all three flagship apps. The rules encode domain models, module ownership, accessibility requirements, and security constraints — so both new engineers and AI tooling have a single source of truth to work from.

Catches architectural drift before human review

AI-first review pipeline

Cursor runs a pre-review pass on every PR before it reaches a human reviewer. It flags missing test coverage, accessibility regressions, and deviations from the architecture rules. This has meaningfully reduced the review round-trips that used to slow down the team on routine PRs.

Fewer review round-trips

Personal experiments

Outside work I use AI as infrastructure, not just a copilot. PaisaTracker runs a persistent agent (Anuradha) that monitors Gmail via IMAP IDLE, parses transactions with DeepSeek, and delivers structured data to Telegram in real time — no manual intervention after setup. I've also built a multi-agent pipeline using Tavily, Firecrawl, and Claude via AWS Bedrock to automate job market research. The pattern in all of these: LLMs as the parsing layer, deterministic code for the rest.

OpenClawDeepSeekClaude APIAWS BedrockTavilyFirecrawlTelegram Bot

Writing

In progress

Coming soon — planning to write about Android internals, AI agent pipelines, and lessons from building for 10M+ users.

Get in touch

I'm open to senior and lead mobile engineering roles — especially where there's interesting platform depth, AI integration, or a small team building something ambitious.

nimishnandwana@gmail.com linkedin.com/in/nimi0112 github.com/nimi0112