About this role
Role Overview: As the Lead full stack Engineer for the new Insight team at Arrive, you will pioneer an AI-First engineering culture from the ground up. You will act as a visionary and principal practitioner, guiding the team in a new paradigm of AI-assisted development. You will lead the technical strategy for a business-critical platform and mentor the team on leveraging advanced AI tools to achieve unprecedented development velocity and creativity. Key Responsibilities: Pioneer an AI-First Development Culture by defining workflows that move beyond simple autocompletion to using generative AI for full-scale prototyping, test-driven development, and complex logic scaffolding. Own the technical vision and architecture for the Discounts platform, making key decisions optimized for an AI-assisted process. Lead by example with AI-native coding, demonstrating mastery in using conversational models and AI-integrated environments. Mentor engineers on prompt engineering and iterative generation using tools like Claude and Cursor. Act as the Engineering Manager's key technical partner to de-risk projects and ensure sound engineering plans. Required Qualifications: 9-11 years of experience in web development using Java/Kotlin and JavaScript technologies. Expertise as a power-user of advanced generative AI tools (Claude, Cursor, Codex) for prototyping, refactoring, and test suite generation. Proven experience designing and building scalable, distributed systems using microservices architecture. Proficiency in Agile principles (Scrum, Kanban), CI, Spring Boot, React, RESTful APIs, PostgreSQL, and cloud platform services. Bachelor’s degree in computer engineering or a relevant field. Preferred Qualifications: Experience with CI/CD, DevOps, Atlassian Suite (Jira/Confluence), Git, and test automation. About Arrive: Arrive is a leading global mobility platform operating in over 90 countries, helping cities and communities make smarter decisions regarding urban mobility through smart payments, optimized parking, and data-driven traffic reduction.