• Identificar tus propios experimentos y lanzarlos al mercado de forma independiente. • Pensar de forma arquitectónica: tomar decisiones sólidas sobre el diseño del sistema sin supervisión constante. • Realizar pruebas de aceptación de usuario (UAT) y control de calidad (QA) de tu propio trabajo: será responsable de la calidad de principio a fin. • Escribir y mantener tus propios archivos de control de IA ( CLAUDE.md , .cursorrules o equivalentes). • Integrar y orquestar múltiples modelos de IA a través de una capa API unificada ( Fal.ai , OpenAI, etc.). • Comunicarse con claridad en inglés: participar en las discusiones sobre el producto, aportar datos y explicar las ventajas y desventajas.

• You'll design and maintain the data infrastructure that powers enterprise analytics and federal reporting for some of the nation's most critical public health programs. • Design, develop, and maintain enterprise ETL pipelines using Azure Data Factory (ADF), Informatica PowerCenter, and Python-based frameworks. • Build and optimize scalable data processing solutions using Python, Spark, and Databricks. • Support Medicaid analytics and federal reporting initiatives including T-MSIS, PERM, MARS, and Quality of Care programs. • Develop robust data validation, reconciliation, and audit-traceable pipelines that hold up under regulatory scrutiny. • Write and optimize SQL and stored procedures across relational platforms including Snowflake, Oracle, and SQL Server. • Participate in cloud migration and modernization initiatives within Azure-based architectures, bridging legacy and modern platforms. • Collaborate closely with analysts, QA engineers, and BI reporting teams to make sure data is accurate, timely, and trustworthy at every stage. • Participate in code reviews, source control, and CI/CD processes using Azure DevOps and GitHub.

• Liderar iniciativas estratégicas de análisis y explotación de datos • Coordinar equipos técnicos en entornos de vanguardia

• Design and develop robust full-stack applications — Node.js services and APIs on the server, and responsive, thoughtfully built interfaces on the client using Vue.js, Next.js, or similar frameworks. • Design and ship AI-native features end-to-end — LLM endpoints, retrieval-augmented generation (RAG) pipelines, tool/function calling, and agentic workflows — that meet the same bar for reliability, observability, and cost-efficiency as the rest of the platform. • Architect and optimize serverless systems on AWS (Lambda, S3, RDS, etc.). • Partner with design and product to turn ideas into crisp, accessible user experiences, and iterate quickly based on customer feedback. • Mentor mid-level and junior engineers and raise the bar through code review, design critique, and a strong team culture. • Collaborate with cross-functional stakeholders to translate business needs into technical solutions. • Monitor, debug, and improve system reliability, performance, and security — including the behavior and cost of AI components in production. • Participate in code reviews, design discussions, and continuous improvement initiatives, leveraging AI coding assistants to accelerate delivery without compromising rigor.