Full Stack Developer - Mobile Developer ( Very strong on Android)
Location: Burlingame, CA (preferred) or Menlo Park CA (secondary) – Onsite || Seattle, WA
Full Time Employment
Full stack Engineer specialized in Mobile development heavy on Android
· Build and ship production-grade web apps using Node.js + React/Next.js
· Develop performant iOS apps with Swift/SwiftUI and Android apps with Kotlin/Jetpack Compose
The Role
We’re looking for a contract Full Stack “Ninja” Developer who can move fast across both web and native mobile platforms. You’ll build full-featured, AI-first user experiences using modern full-stack frameworks (e.g. Node.js + React/Next.js) and native mobile stacks (Swift for iOS, Kotlin for Android), all integrated with scalable AI backends and robust cloud infrastructure.
Key Responsibilities
· Build and ship production-grade web apps using Node.js + React/Next.js
· Develop performant iOS apps with Swift/SwiftUI and Android apps with Kotlin/Jetpack Compose
· Integrate AI capabilities: LLM APIs, tool use, vector DBs, memory, retrieval-augmented generation (RAG), and evaluation loops
· Design secure, scalable backend services in JavaScript/TypeScript or Python to orchestrate agentic workflows
· Deploy on AWS or GCP, using Docker, CI/CD, observability tooling, and IaC (Terraform or CDK)
· Rapidly prototype, iterate, and polish features in tight collaboration with product, research, and design
Qualifications
· Deep experience with Node.js, React, and modern frontend architecture
· Native app development expertise in Swift/SwiftUI (iOS) and Kotlin/Jetpack Compose (Android)
· Backend experience with Node.js, Python, FastAPI, Next.js, LangChain, or similar frameworks
· Familiarity with cloud platforms (AWS or GCP), containerization, IaC (Terraform/CDK), and continuous delivery pipelines
· Strong product instincts and a passion for building clean, performant cross-platform apps
· Demonstrated success shipping AI-first features or applications powered by LLMs or agent frameworks
Bonus Points
· Experience using AI development tools like Claude Code, Cline, or Copilot++ in production
· Familiarity with AI/ML infrastructure and workflows, including:
· Model training and fine-tuning pipelines using PyTorch or JAX
· On-device inference with Core ML, NNAPI, or quantized model deployment
· High-performance systems experience with C/C++, Rust, or Go for native modules, low-latency pipelines, or WebAssembly
· Familiarity with the latest developments in AI technologies