• Build and maintain iOS applications using Swift and SwiftUI. • Integrate AI-powered features through backend APIs. • Design UX patterns for AI interactions, including loading states, streaming responses, retries, and fallbacks. • Optimize performance, memory usage, and battery efficiency. • Capture user signals and feedback to support AI evaluation and iteration. • Collaborate closely with backend and ML engineers on API design and system behavior. • Maintain high App Store quality, stability, and production reliability.

• Own the application engineering strategy and execution across backend, mobile, and desktop. • Lead and grow a small, senior applications team, including backend, mobile, and desktop engineers. • Set the architectural direction for AI-powered product workflows, APIs, and client integrations. • Ensure AI capabilities are integrated into the product with clear abstractions, predictable behavior, and graceful failure modes. • Partner closely with Machine Learning leadership to translate model capability into shippable product features. • Make high-impact decisions across latency, cost, reliability, security, and user experience. • Establish a strong execution culture through code reviews, design reviews, and hands-on technical leadership. • Ensure production readiness: observability, monitoring, retries, fallbacks, privacy, and cost controls. • Balance speed and discipline – shipping quickly without compromising long-term system quality.

• Own the application engineering strategy and execution across backend, mobile, and desktop. • Lead and grow a small, senior applications team, including backend, mobile, and desktop engineers. • Set the architectural direction for AI-powered product workflows, APIs, and client integrations. • Ensure AI capabilities are integrated into the product with clear abstractions, predictable behavior, and graceful failure modes. • Partner closely with Machine Learning leadership to translate model capability into shippable product features. • Make high-impact decisions across latency, cost, reliability, security, and user experience. • Establish a strong execution culture through code reviews, design reviews, and hands-on technical leadership. • Ensure production readiness: observability, monitoring, retries, fallbacks, privacy, and cost controls. • Balance speed and discipline – shipping quickly without compromising long-term system quality.

• Enhance the existing chatbot with HR-specific use cases. • Integrate GenAI functionalities (e.g., LLM-based response generation, RAG flows, prompt optimization). • Further develop the current bot infrastructure using modern Python frameworks (e.g., FastAPI). • Develop and customize microservices, including comprehensive field validations. • Design and implement interfaces between existing DEUTZ systems. • Set up logging, monitoring, and diagnostic structures. • Implement CI/CD automations. • Develop Python/React applications (frontend development optional/supportive). • Create technical documentation for architecture, processes, and interfaces.