• Lead an engineering team with diverse levels of experience and expertise – with a focus on integrating AI into our existing products and working on new AI-powered offerings. • Collaborate effectively with product managers, ML and QA engineers, stakeholders, and senior developers to shape and deliver the roadmap. • Contribute to the product roadmap and participate in the feature design process. • Constantly refine team processes and culture to ensure smooth delivery and agility. • Act as a coach rather than a manager who’s detached from hands-on work – spending some time personally designing and working on technical tasks and software architecture. • Rapidly assimilate extensive technical information and dive deep into mature codebases. • Coach your team members on their technical and soft skills and provide them with feedback to help them improve every day.

• Develop and train AI models and deploy them to production; • Integrate these models/AI systems with other systems and platforms; • Diagnose and resolve complex AI technical issues; • Define technical standards for integrating and using AI in production; • Lead adoption of best practices for AI operations and monitoring (MLOps); • Share knowledge with the team and at events; • Serve as a technical reference in strategic AI discussions.

• Create SAS, SQL, Python, and R programs to prepare raw NCHS, BRFSS, SENSOR Pesticide, and Occupational Hearing Loss data for NIOCCS. • Generate files, split datasets, create data quality reports, and upload files for coding and human review. • Build .NET tools (e.g., bulk upload apps, new Admin System API lookup forms, auto-downloader apps). • Create Python programs interacting with the NIO API to test coding, generate outputs, and support external partners. • Test, debug, and refine the new NIO API parameters, outputs, and integration with external systems.

• Entrega y calidad del producto • Construir soluciones de alta calidad orientadas al impacto en el cliente y el negocio. • Garantizar la calidad técnica mediante la estrategia de pruebas y controles en CI. • Asegurar el despliegue y liberación de cambios al usuario final. • Decisiones técnicas y arquitectura • Decidir sobre diseño de APIs, patrones de integración y gestión de deuda técnica. • Coordinar con otros equipos contratos compartidos y cambios con impacto cruzado. • Identificar riesgos técnicos y proponer estrategias de mitigación. • IA y automatización • Integrar IA y agentes en el ciclo de desarrollo de forma responsable y efectiva. • Evaluar el uso de IA versus desarrollo tradicional según impacto, costo y riesgos. • Compromiso con el negocio • Comprender los indicadores del negocio y el impacto del trabajo en la compañía. • Identificar y comunicar riesgos en la ejecución del plan de desarrollo.