• Design, build, and maintain RESTful and event-driven microservices in Java. • Own and extend integrations with third-party platforms — CRMs, EMRs, marketing automation, and analytics tools. • Build and maintain data pipelines that move, transform, and deliver structured data reliably. • Instrument services for observability (logging, tracing, alerting) and participate in on-call rotation. • Lead technical initiatives: scope the work, surface blockers early, and pull in what you need to ship. • Participate actively in code reviews — explain your design decisions clearly, incorporate feedback constructively. • Communicate technical trade-offs and progress clearly and concisely to both engineering peers and non-technical stakeholders.

• 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

• 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.