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Finom is seeking a Senior iOS Engineer to design and build features for our iOS app used by European business owners. You will own end-to-end delivery, shape architecture, and mentor peers in a cross-functional team including Backend, ML/AI, QA, Design, and Product.
We value Swift/SwiftUI/UIKit mastery, VIPER and Coordinator patterns, and strong testing and CI/CD discipline. Finom emphasizes product impact and high-quality engineering in a fintech context.
You're pragmatic and have a proven track record of shipping products that matter. You communicate clearly across disciplines and thrive in a cross-functional environment where everyone is solving the same customer problem togetherExperience with layout development in code, particularly using SnapKit or similar toolsConfidence with Git / GitLab, including the ability to set up and use GitLab CI/CDStrong knowledge of the Swift language and at least 3 years of commercial iOS developmentPractical experience using the VIPER architectural pattern and the Coordinator navigation patternA builder's mentality — you care about the product, the users, and the outcomes, not just the codeDeep understanding of OOP, SOLID principles, and design patternsExcellent knowledge of UIKit and experience (or a strong desire to develop skills) with SwiftUIAbility to write unit and UI testsBackground in fintech or experience with financial products — you understand the stakesClear, concise communication in English across technical and non-technical audiencesSolid grasp of mobile security best practices (especially critical in our domain)Experience profiling and optimizing UI performance — reducing rendering bottlenecks and achieving smooth 60/120fps on iOSHands-on work with performance tooling: Instruments, XCTest, or similarPublished apps on the App Store you're proud ofAn active GitHub profile with code you're happy to shareHands-on experience with AI agents and LLM tools (Claude, Cursor, Copilot, etc.) — setting up agent environments, writing prompts, skills, and behavioral rulesUnderstanding of model capabilities and limitations — knowing which model fits which task and how to manage the context window effectiveExperience with AI-powered IDE tools (Cursor, Windsurf, GitHub Copilot, Claude Code, etc.) — including agent mode, rules files configuration, and integrating AI into the daily development workflowAbility to evaluate and verify AI-generated output — using automated tests, linters, and critical review to catch hallucinations and errorsAwareness of AI security risks — prompt injection, data leakage, and safe handling of untrusted inputs in agentic workflows