Senior AI-Native Product Engineer, Mobile

About the team

The Mercury Mobile team builds Zillow Instant Messaging (ZIM) — the conversation layer where millions of movers participate in a multiplayer, integrated experience to find their next home. We own the messaging experience on both iOS and Android, from the real-time messaging core through the rich, interactive content inside every conversation. Our larger organization is responsible for turning interest in a home into a completed tour, a durable relationship with an agent, and a successful move. Right now we are rebuilding what a messaging product can be when an AI assistant is a participant in the conversation rather than a feature bolted onto it.

About the role

As a Senior Software Development Engineer on Mercury Mobile, you will define how AI shows up inside ZIM on mobile — and you will do it on both platforms. This is deliberately a cross-platform role: you will work in Swift and Kotlin, and the architectural decisions you make will land on iOS and Android together rather than diverging. The problems are the interesting ones in mobile client engineering today: streaming AI responses into a live conversation without janking the UI, rendering multi-modal and richly structured content that exceeds what a message bubble was ever designed to hold, and building it all to work on a spotty connection in a driveway. You will have real ownership of the architecture, and a team that expects you to use it.

You Will Get To

• Design and ship the mobile client architecture for AI in conversations — streaming responses, topic-based conversation structures, and multi-modal content rendering across iOS and Android
• Own cross-platform architectural decisions for the ZIM messaging core, keeping Swift and Kotlin implementations converged rather than letting them drift
• Build real-time, resilient messaging experiences that hold up on unreliable mobile networks, with observability and SLOs you define
• Partner directly with the AI, Web, and Backend teams shaping Zillow’s conversational AI roadmap, and represent mobile in those decisions
• Use AI coding agents as a genuine part of your workflow — and help set the standards for how the team does it well
• Raise the bar on testing and delivery velocity through unit, snapshot, and UI automation, and shared tooling other teams adopt
• Mentor engineers across both platforms and grow the team’s cross-platform depth

This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions.In California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC the standard base pay range for this role is $160,900.00 - $257,100.00 annually. This base pay range is specific to these locations and may not be applicable to other locations.

In Colorado, Hawaii, Illinois, Maine, Minnesota, Nevada, Ohio, Rhode Island, Vermont, and Virginia the standard base pay range for this role is $152,900.00 - $244,300.00 annually. The base pay range is specific to these locations and may not be applicable to other locations.In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location. Actual amounts will vary depending on experience, performance and location. Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.

Who you are

• You have 5+ years building and shipping native mobile applications at consumer scale, with a deep understanding of the app lifecycle
• You have production experience on both iOS and Android — or deep expertise in one platform and demonstrated delivery in the other
• You are fluent in Swift and Kotlin, and comfortable in SwiftUI and Jetpack Compose
• You have built features on top of real-time or streaming data, and you know where the hard parts are
• You have integrated GraphQL clients and reasoned carefully about caching and cache invalidation
• You use AI coding agents on real production work and have a considered point of view on where they help and where they do not
• You have owned the architecture of a module or platform that other teams depended on, and you write the documentation that makes adoption possible
• You …