• Diseñar, desarrollar y mantener aplicaciones y servicios de software con capacidades de IA agéntica. • Implementar flujos de trabajo basados en agentes inteligentes, integraciones, lógica de negocio y automatización. • Construir e integrar APIs, servicios, microservicios y componentes backend/frontend según el alcance del proyecto. • Participar en el diseño técnico de soluciones orientadas a escalabilidad, seguridad y mantenibilidad. • Integrar modelos, herramientas de IA, motores de decisión y fuentes de información empresariales. • Asegurar calidad del código mediante pruebas, documentación y buenas prácticas de desarrollo. • Colaborar con equipos de arquitectura, datos, producto, procesos y negocio. • Identificar mejoras de desempeño, confiabilidad y evolución de las soluciones implementadas.

• Diseñar, desarrollar y mantener aplicaciones y servicios de software con capacidades de IA agéntica. • Implementar flujos de trabajo basados en agentes inteligentes, integraciones, lógica de negocio y automatización. • Construir e integrar APIs, servicios, microservicios y componentes backend/frontend según el alcance del proyecto. • Participar en el diseño técnico de soluciones orientadas a escalabilidad, seguridad y mantenibilidad. • Integrar modelos, herramientas de IA, motores de decisión y fuentes de información empresariales. • Asegurar calidad del código mediante pruebas, documentación y buenas prácticas de desarrollo. • Colaborar con equipos de arquitectura, datos, producto, procesos y negocio. • Identificar mejoras de desempeño, confiabilidad y evolución de las soluciones implementadas.

• The core of this role is helping network partners harness AI to deepen and accelerate their impact. This person will keep a close pulse on how partners are innovating, help them innovate more, and ensure they are doing it safely, which includes: • 1:1 advisory and consulting support: Meet regularly with partners to understand their AI ambitions and challenges, provide tailored guidance, and help them develop and strengthen their AI strategies and practices • Learning experiences and community spaces: In collaboration with others, create and facilitate virtual and in-person learning communities and convenings for CEOs, heads of technology, and other leaders around topics such as child safety, AI innovation, and AI policy • Capturing and sharing insights: Proactively learn from partner innovations across the network and make key insights, case studies, and resources available via the network portal; connect partners pursuing similar questions so they can learn from each other • Collaboration with programmatic specialists: Work alongside functional specialists (e.g. in teacher training, alumni, selection) to bring an AI lens to their communities and help catalyze conversations about how AI can strengthen specific programmatic functions • Build and buy guidance: In collaboration with IT colleagues, help partners think through what to build vs. buy; stay current on the landscape of AI tools and surface recommendations for technologies that could address consistent partner needs • Subgrant fund: Explore the possibility of creating a fund to enable partners’ AI innovation, and collaborate with colleagues on the sub-granting team to define the parameters of that fund and to act as the programmatic lead for the fund • Network standard for responsible AI use: Ensure partners have the resources, frameworks, and support they need to meet Teach For All's network standard for safe and values-aligned AI use, including on topics such as child safeguarding, data privacy, and AI governance • AI innovation is happening across Teach For All's global organization. This role will help ensure those efforts are mutually reinforcing rather than siloed: Convene the people across our organization working on AI (e.g., teachers, alumni, cross-border learning, internal team tech innovation, and more) to ensure we are advancing holistically and communicating clearly about our collective progress • Inspire and connect internal teams, helping surface what we are each learning and identifying opportunities for greater coherence and collaboration

• Set the multi-year strategy for ML, data, and BI • Build and scale the Data Science / AI, Data Engineering, and BI Engineering organization • Manage managers and tech leads • Run performance management, career development, and retention • Operate as a peer to VP-level leaders across various functions • Own the architecture, deployment, and operation of the production ML