• Lead the design and implementation of features across frontend, backend, integrations, and data layers • Act as the technical authority for the team, reviewing code, guiding architectural decisions, and approving changes • Drive improvements in code quality, security, testing, and release processes • Use AI-assisted development tools to improve delivery speed, reduce technical debt, and enhance product development • Identify risks early, break down work effectively, and support predictable sprint delivery • Mentor and support developers, helping raise overall team capability and engineering standards • Collaborate with stakeholders to translate business requirements into robust technical solutions • Take ownership of production systems, ensuring stability, performance, and continuous improvement • Contribute hands-on to development, including refactoring and improving existing codebases • Help reduce support overhead by improving system reliability and resolving root causes

• Product development from day one: You develop our digital products and SaaS solutions across the entire lifecycle — from the idea and architecture through implementation to production operation. • Full-stack development: You work on both the frontend (e.g., Angular) and the backend (.NET, APIs, databases) and ensure a clean interaction between all components. • Technical co-design: You actively contribute to architecture, technology and design decisions and help shape our platforms so they are sustainable and maintainable. • Quality & sustainability: You value clean code, tests, code reviews and high software quality, focusing on long-term product development rather than short-term fixes. • Close teamwork: You collaborate closely with other developers, product owners and, when applicable, customers to understand requirements and translate them into working solutions. • Continuous improvement & scaling: You help continuously evolve and optimize our products and prepare them for growth and scaling.

• Serve as a technical leader and architect for developing advanced reverse logistics and warehouse management solutions using Microsoft technologies • Mentor and guide engineering teams to ensure adherence to best practices in software design, coding, and architecture • Collaborate with cross-functional teams to align software solutions with business objectives, operational needs, and regulatory requirements • Design and implement systems to manage pharmaceutical returns, recycling, and disposal in compliance with DSCSA, FDA, and other relevant regulations • Develop warehouse management systems (WMS) to optimize space utilization, inventory tracking, order fulfillment, and real-time reporting • Create APIs and integrations to connect warehouse systems with pharmacy management platforms, supply chain tools, and external logistics providers • Utilize Azure cloud services and containerization tools like Docker and Kubernetes to build scalable, fault-tolerant systems • Implement CI/CD pipelines to streamline development, testing, and deployment processes for reverse logistics and warehouse management software • Ensure all software solutions comply with healthcare and pharmacy regulations, including DSCSA, FDA, HIPAA, and environmental guidelines • Monitor and improve system performance to support high transaction volumes, real-time inventory tracking, and data processing • Incorporate AI/ML-driven insights to enhance warehouse efficiency, predict product returns, and optimize reverse logistics processes

• Act as a player-coach, combining system design and mentorship with active contribution to the codebase (primarily Python/PyTorch) • Own and continuously improve the core conversational loop, including context management, retrieval systems (RAG), and inference performance • Guide and develop a small team of AI engineers while maintaining a high bar for execution • Define and execute the approach to model improvement, including supervised fine-tuning and preference optimization techniques • Oversee data pipelines, including dataset sourcing, labeling, and quality control to improve model performance across different user contexts • Design and implement custom classification systems capable of detecting and filtering harmful or non-compliant content • Build nuanced moderation layers that go beyond binary decisions, enabling context-aware handling within a complex content environment