• Lead and build features end-to-end: from reviewing user interviews and product design, through architection and building systems to deployment and monitoring in production. • Partner closely with our product team to discover user problems and shape their solutions - creating a world class experience for our organizers and travelers. • Write high-quality, maintainable code across both frontend (TypeScript/React) and backend (Ruby on Rails). • Ensure our services are always on by building resilient applications, ensuring they are well monitored and mitigating incidents as an on-call/incident responder. • Mentor teammates and contribute to WeTravel’s engineering practices and excellence.

• Writing/testing code for back-end operations, monitoring architecture performance, troubleshooting and resolving issues. • Design, build, test and maintain scalable technology solutions to meet business needs. • Implement new features, new products, and help to improve existing features. • Perform or direct revision, repair, or expansion of existing programs to increase operating efficiency or adapt to new requirements. • Consult with managerial, engineering, and technical personnel to clarify program intent, identify problems, and suggest changes. • Perform systems analysis and programming tasks to maintain and control the use of computer systems software as a systems programmer. • Compile and write documentation of program development and subsequent revisions, inserting comments in the coded instructions so others can understand the program. • Consult with and assist computer operators or system analysts to define and resolve problems in running computer programs.

• Write production-level code in Java (with AI tools) • Prompt engineering and testing with LLMs, including Claude, Gemini, and OpenAI models • Context engineering to determine the right data • Agentic workflow design • Help us build systems to easily monitor and test LLM performance • Design and implement solutions for scale and maintainability across multiple clients • Contribute as a thought leader to conversations around LLM usage

• Temporal workflows that orchestrate multi-step AI operations • Backend services in Clojure that integrate with LLM APIs • Data models and PostgreSQL schemas that support complex enrichment pipelines • RAG pipelines using Qdrant for semantic search • APIs and data pipelines that deliver enriched catalogs to retailer PDPs