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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Mobile App Developer - **Company:** Zion Church - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $70,040 - $108,150 - **Contract:** Permanent contract - **Skills:** Flutter, Java (Programming Language), A/B Testing, Artificial Intelligence, Amazon Web Services, Application Integration Architecture, App Store (IOS), Unit Testing, Microsoft Azure, Software Bug Management, Mobile Application Development, Databases, Continuous Integration, Mobile Application Software, Python (Programming Language), Machine Learning, Node.Js, NoSQL, Recommender Systems, OpenAI, Tensorflow, Azure Machine Learning, Secure Coding, SQLite, SQL Databases, Software Vulnerability Management, Datadog, Data Processing, Model-Driven Development, Chatbots, Swiftui, On-device Inference, Delivery Pipeline, Large Language Models, Prompt Engineering, Generative AI, Firebase, Backend, Kotlin, AI Platforms, Core Data, Information Technology, Sentry, Jetpack Compose, React Native, Tools for Reporting, Azure AI, Code Restructuring - **Published:** November 7, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=a189eeb99d3b8364 ## About the Role * Bachelor's degree in Computer Science, Engineering, or a related field. * 5+ years of professional experience in mobile application development. * Proficiency in mobile frameworks such as Swift/SwiftUI, Kotlin/Jetpack Compose, React Native, or Flutter. * Demonstrated, hands-on experience integrating AI/ML models or AI-powered services into mobile applications, not just backend or web systems. * Familiarity with consuming LLM APIs (such as OpenAI, Anthropic, or similar) from a mobile client, including handling streaming responses and token-based interactions. * Working knowledge of on-device machine learning tools such as Core ML, ML Kit, TensorFlow Lite, and an understanding of when on-device versus server-side inference makes sense. * Expertise in consuming backend APIs built with languages such as Python, Node.js, or Java. * Strong experience with local and remote database technologies (SQLite, Core Data, Realm, and cloud-backed SQL/NoSQL). * Experience with cloud platforms such as AWS, Azure, or GCP, including AI/ML services offered by those platforms (SageMaker, Vertex AI, Azure AI, or similar). * Manage app store deployment pipelines, CI/CD automation, and mobile release processes for reliability and scalability. * Experience writing and maintaining unit tests, UI tests, and automated test suites, including tests that account for non-deterministic AI outputs. * Competence in mobile monitoring and crash reporting tools (Sentry, Firebase Crashlytics, Datadog) to ensure uptime and performance, including monitoring for AI service latency/failures. * Deep knowledge of secure coding practices, vulnerability mitigation, and encryption techniques on mobile platforms, including secure handling of data sent to and from AI models., * Prior experience shipping a consumer-facing mobile app with a chat-based or conversational AI feature. * Experience with vector databases or retrieval-augmented generation (RAG) patterns as consumed from a mobile client. * Familiarity with prompt engineering fundamentals, even if primarily working on the client side. * Experience with A/B testing or feature flagging systems specifically for iterating on AI-driven features. ## Description * Develop and maintain mobile applications for iOS and Android platforms. * Build new features for Pocket Discipleship, including user-facing interfaces, local data handling, offline support, and integration with backend and AI services. * Conduct bug fixes and refactor code to improve app performance, stability, and responsiveness. * Consume and help design robust APIs to facilitate communication between the mobile app, backend services, and AI models. * Work closely with product managers and designers to translate product requirements into technical specifications and a polished mobile user experience. * Participate in the entire mobile development lifecycle, from concept and design to app store deployment and maintenance. AI Integration * Collaborate closely with our AI team to integrate AI models and services directly into the mobile experience, including LLM-powered chat and conversational features, recommendation engines, and personalization systems. * Build mobile-side logic to consume AI model outputs in real time, including handling streaming responses, latency, and graceful fallback when AI services are unavailable. * Optimize on-device performance for AI-powered features, balancing responsiveness, battery usage, and data consumption. * Implement and maintain prompt-based or model-driven UI states, ensuring the interface can adapt to dynamic, AI-generated content. * Work with the AI team to test, validate, and iterate on AI feature behavior from the mobile client's perspective, including edge cases and unexpected model outputs. * Stay current on mobile-specific AI tooling and SDKs (such as on-device inference frameworks, Core ML, ML Kit, or similar) and recommend where they can improve app performance or reduce dependency on server calls.