• Design, architect, build, and maintain backend services and APIs using Python, Postgres, FastAPI, and Temporal • Design and optimize database solutions • Write strong unit tests and help drive engineering quality • Apply DevOps practices across CI/CD, deployment, monitoring, and reliability • Take ideas from concept to production and continuously improve them • Use AI to accelerate development and improve engineering productivity • Troubleshoot production issues and implement durable fixes

• Develop robust, scalable, and secure backend solutions (preferably in Go), working at the core of our platform. • Drive the evolution of our service architecture by proposing improvements and promoting long-term vision. • Actively collaborate in building technical processes, standards, best practices, and automations. • Investigate complex problems, propose intelligent solutions, and anticipate risks and impacts. • Work closely with Product, Design, and other areas to deliver high-impact solutions for doctors, patients, and partners. • Ensure quality in deliveries through testing, documentation, and attention to performance. • Contribute ideas, participate in technical discussions, and perform code reviews to raise the team’s technical level.

• Build systems to add features across our Network API Platform • Create scalable microservices that will help support our impressive growth • Write efficient and scalable code, in well-tested systems • Develop on a public cloud infrastructure

• Lead the design and development of new solutions using Generative Artificial Intelligence (LLMs) to enhance the shopping experience and management workflows for our customers; • Integrate and orchestrate AI APIs (such as OpenAI, Anthropic, Gemini, etc.) within our microservices-based architecture; • Apply advanced AI techniques such as prompt engineering, RAG (Retrieval-Augmented Generation) and fine-tuning, ensuring responses are accurate and high-performing; • Actively research and propose innovative solutions that use AI to solve real pain points for merchants and end consumers; • Ensure scalability, security and cost optimization of integrations with language models; • Perform code reviews, refactorings and promote AI development culture and best practices across the team; • Develop unit and integration tests focused on the reliability of AI responses.