AI-First Android Engineer

Grove Collaborative is a sustainability-focused consumer products company creating household and personal care essentials that are effective, beautifully designed, and healthier for people and the planet. We are a certified B Corp, plastic-neutral, and on a mission to transform the CPG industry for good.

THE ROLE

Grove is hiring an AI-First Android Engineer — a senior, single-threaded owner of our Android surface who operates as an “engineer-as-a-team.” This isn’t a role where you hand-write every line and lean on AI for autocomplete. This is a role where AI is your primary instrument: you direct fleets of coding agents, generate, review, and refactor at orders of magnitude beyond what a traditional engineer can produce, and take total ownership of features end-to-end — from discovery through production. You will be measured by what ships, what stays up, and what customers feel — not by lines of code or tokens used.

You operate in a new-world environment where one well-equipped engineer can deliver the output of a small team. We expect you to compound your own leverage every quarter: better prompts, better evals, better agent harnesses, better guardrails. The bar isn’t “uses AI tools.” The bar is “runs AI like a team you manage.”

WHAT YOU’LL OWN

• Direct multiple AI coding agents in parallel to design, build, test, and ship Android features in Kotlin against the Android SDK.
• Take total ownership of a slice of the Android app — discovery, scoping, architecture, implementation, QA, release, monitoring, and iteration.
• Run an “engineer-as-a-team” workflow — spawn agents for spec drafting, codegen, test generation, code review, refactoring, doc writing, and bug triage, then merge, judge, and ship.
• Develop and defend a strong point of view on what good Android code looks like inside Grove’s architecture (Clean Architecture, multi-module Gradle with base/middleware/data/app, MVVM with DataBinding, Koin for DI, Coroutines/Flow, Moshi) so you can critically review AI output and reject what doesn’t meet our bar.
• Design prompts, evals, and harnesses that make AI-assisted mobile development repeatable and measurable, not artisanal.
• Stand up automation that closes the loop: Fastlane lanes, CircleCI checks, AppCenter/Play Console distribution, device test farms, telemetry-driven rollback, and AI-powered review gates.
• Drive architecture decisions with AI as a research and prototyping partner — explore three options in a day instead of one in a week, including the path to introducing Jetpack Compose into a DataBinding/XML codebase.
• Collaborate with other engineers on architecture and trade-offs — bring designs for review before you ship them. Solicit business context from PMs, designers, and platform engineers; don’t guess in isolation.
• Own production health autonomously — monitor Sentry, Datadog, Cloudflare, and Firebase to asses