• Liderar técnicamente células de desarrollo enfocadas en aplicaciones móviles híbridas con React Native. • Definir lineamientos de arquitectura, buenas prácticas de desarrollo y estándares de calidad. • Diseñar e integrar servicios backend, APIs REST, microservicios y componentes de integración. • Coordinar la comunicación técnica entre equipos mobile, backend, QA, arquitectura, seguridad e infraestructura. • Asegurar la correcta integración con sistemas bancarios, plataformas legacy y servicios empresariales. • Revisar código, validar entregables técnicos y promover buenas prácticas de desarrollo. • Participar en la estimación técnica, planeación de sprints y definición de historias técnicas. • Apoyar en la resolución de incidentes complejos, análisis de causa raíz y estabilización de ambientes. • Garantizar la trazabilidad, consistencia y seguridad de la información en los procesos de integración. • Impulsar la mejora continua, automatización y eficiencia operativa del equipo.

• Design and build autoscaling systems for storage clusters • Own the infrastructure-as-code stack (Terraform) on AWS • Build self-healing automation • Develop CI/CD pipelines and deployment tooling for storage services • Design and implement observability for the entire storage platform • Own cluster management tooling • Drive performance and cost optimization across the storage data path • Partner with product engineering to define scalability limits and load test new features • Contribute to incident response and lead blameless post-mortems

• Drive generative and agentic AI from ideation through to deployment. • Own evaluation and quality: confidence scoring, accuracy measurement, and regression testing. • Instrument the data flywheel from day one: capture every AI draft and every final output. • Build the product end-to-end, including automations and integrations. • Work forward-deployed using modern LLMOps practices and closely with live deliveries.

• Design and build the backend services (primarily Go, Java, and Python) that run AI and model inference on real-time data. • Own features end to end — drafting the design, aligning stakeholders inside and outside the team, and driving the decision to a conclusion. • Make the technical calls on systems that span teams: model lifecycle, inference routing, and agent execution. • Own the quality of what you ship — code, test coverage, documentation, operability, and rollout safety. This is production infrastructure serving live inference, so reliability isn't an afterthought. • Make the engineers around you better through code review, design feedback, and being someone the team trusts with ambiguous, cross-cutting work. • Participate in on-call for the services your team owns, and help keep the team's processes and rituals healthy.