• Help train large language models (LLMs) to write production-grade code • Compare and rank multiple code snippets • Repair and refactor AI-generated code • Inject feedback into the RLHF pipeline

• Act as a main technical contributor and decision-maker for the platform modernisation initiative • Drive the migration, ensuring clean, maintainable, and scalable architecture • Review, validate, and influence system and application architecture to support performance, scalability, and long-term growth • Lead by example in hands-on development, code reviews, and technical problem-solving • Influence and improve engineering standards, code quality, and delivery practices • Collaborate closely with the client developers and product stakeholders • Support and oversee CI/CD processes in Azure DevOps, ensuring reliable and secure deployments • Identify technical risks and bottlenecks early and propose pragmatic mitigation strategies • Mentor other engineers where needed and contribute to a healthy, professional engineering culture

• Participar en la planificación PI de SAFe • ceremonias de sprint • discusiones de diseño colaborativas • Desarrollar y desplegar microservicios basados en .NET Core en AWS • trabajar en capas de frontend, backend y datos • consumir plantillas CDK proporcionadas por Cloud Engineering • asegurar el rendimiento del servicio, la observabilidad y la mantenibilidad • contribuir a pruebas unitarias, documentación de API y mejores prácticas de ingeniería • colaboración con equipos remotos a través de diferentes zonas horarias

• Investigate, diagnose, and resolve bugs in a vanilla PHP application. • Debug complex issues across application logic, database interactions, and integrations. • Deliver safe, well-tested fixes that minimize regression risk. • Take ownership of assigned features or components from development through release. • Write clear comments and documentation to support maintainability. • Collaborate with QA and Support to reproduce reported issues and validate fixes. • Analyze logs, error reports, and monitoring data to identify root causes. • Ensure fixes align with existing system behavior and user expectations. • Assist with minor performance improvements and reliability enhancements. • Participate actively in code reviews and technical discussions. • Apply agreed-upon standards for code quality, testing, and deployment. • Use AI-assisted development tools (such as CursorAI, GitHub Copilot, or similar) to accelerate development, testing, and documentation. • Contribute incremental improvements to shared utilities or internal tooling when beneficial.