Build high-impact AI capabilities into native iOS applications, integrating LLM-powered services and on-device Core ML with a focus on latency, offline capability, cost, and user privacy
Prototype and evaluate emerging iOS frameworks and mobile AI technologies, providing technical recommendations for production adoption
Profile, diagnose, and resolve runtime performance bottlenecks to ensure fluid application responsiveness across supported devices
Collaborate cross-functionally with Product, UX, and Systems teams to translate complex business problems into reliable technical designs
Author and maintain high-quality technical documentation, architectural decision records, and system diagrams
What You Bring
Bachelor’s degree in Computer Science, a related field, or equivalent practical experience
Demonstrated experience in software engineering, with expertise in test-driven development, robust design practices, and distributed systems for enterprise iOS apps
Deep hands-on proficiency in Swift, native iOS development, and standard mobile architectural patterns (e.g., MVVM, Clean Architecture, VIPER)
Practical experience integrating AI/ML capabilities into mobile applications, including LLM APIs, Core ML, or on-device inference tooling
Solid understanding of responsible AI deployment, focusing on data privacy, security perimeters, and mitigation of non-deterministic model outputs
Experience utilizing AI coding tools in daily engineering workflows with sound technical judgment in verifying generated code
Familiarity with enterprise microservices integration patterns, event-driven architectures, and API gateway communication
Comprehensive experience with modern SaaS lifecycles, including CI/CD pipelines, automated testing, deployment, and production observability
