• Diseñar, construir y operar una gateway de LLMs que ofrezca una interfaz unificada sobre múltiples proveedores • Implementar enrutamiento de modelos, fallbacks , reintentos, balanceo y selección dinámica de proveedor/modelo por caso de uso • Gestionar credenciales y claves de proveedores de forma segura (rotación, secrets management) • Implementar caching (incluido semantic caching ) para reducir costos y latencia • Construir y operar una gateway de MCP para exponer, descubrir y gobernar el acceso a servidores y herramientas MCP • Definir controles de acceso por herramienta/servidor (qué app o equipo puede invocar qué) • Auditar y registrar el uso de herramientas MCP, con trazabilidad de extremo a extremo • Implementar guardrails , filtrado de contenido y defensas contra prompt injection y fuga de datos • Implementar redacción/enmascaramiento de datos sensibles (PII) en prompts , respuestas y logs • Definir y aplicar políticas de acceso (RBAC), cuotas y límites de uso por equipo, app o usuario • Mantener registros de auditoría y apoyar requisitos de cumplimiento y privacidad • Implementar atribución de costos por equipo/app/feature y presupuestos con alertas • Construir observabilidad para IA: tracing , métricas de latencia, costo, uso y calidad • Establecer dashboards y alertas sobre consumo, errores y degradación de proveedores • Definir SLAs/SLOs para la plataforma de IA y planes de respuesta ante incidentes (incluida la caída de un proveedor) • Apoyar a los equipos de producto e ingeniería en la integración con la gateway

Role Description Projeto de inovação do INSTITUTO ITAÚ DE CIÊNCIA, TECNOLOGIA E INOVAÇÃO em parceria Inova Talentos. Atividades: - Desenvolver e implementar arquiteturas de agentes comparáveis (single, multiagente centralizado, descentralizado e híbrido) em ambiente experimental - Construir suíte de tarefas financeiras simuladas com critérios objetivos de avaliação - Instrumentar métricas de desempenho, custo, latência e coordenação entre agentes - Conduzir experimentos controlados e análises estatísticas comparativas - Desenvolver modelo preditivo para recomendação de arquitetura com base nas características das tarefas Qualifications - Modalidade: TECH 4 Doutor - Formação: Doutorado - Cursos: Ciência da Computação, Engenharia, Estatística, Matemática Aplicada, Ciência de Dados ou áreas correlatas Requirements - Programação avançada em Python - Experiência com machine learning e/ou modelos de linguagem (LLMs) - Conhecimento em experimentação e análise de dados - Familiaridade com arquitetura de sistemas distribuídos ou agentes Benefits - Disponibilidade: 40h semanais - Duração: 12 meses - Bolsa Auxílio: R$ 11.000,00 - Atuação: Remota Company Description Conheça o INOVA TALENTOS - Vídeo 1 - Vídeo 2

Role Description Cisco is currently seeking two senior product marketing leaders to join our team. These are remote roles based in the United States, requiring significant travel (approximately 30–50% of the time). In these roles, you will own the product marketing strategy for Cisco’s AI infrastructure portfolio, connecting technical capabilities to the business outcomes customers require for AI workloads and AI-native applications. You will: - Define the narrative, positioning, messaging, launch strategy, and sales enablement required to power secure, connected, AI-ready organizations. - Partner with Product Management, Engineering, Sales, Corporate Marketing, Analyst Relations, and Communications. - Translate complex infrastructure innovation into market value. - Drive cross-functional alignment. - Equip the business to win with enterprise buyers and executives. Qualifications - Bachelor’s degree in Business, Engineering, Marketing, Communications, or a related field, or 19+ years of equivalent professional experience. - 15+ years of experience in B2B technology marketing. - 5+ years of experience in product marketing leadership specifically within enterprise infrastructure, networking, data center, cloud, security, or AI/ML platforms. - 5+ years of experience developing product positioning, messaging, go-to-market strategy, launch plans, and sales enablement assets for enterprise technology solutions. Requirements - Ability to travel domestically and internationally up to 50% of the time. - Experience working directly with product and engineering teams to translate technical roadmaps into customer-facing value propositions. - Experience leading cross-functional initiatives involving sales, marketing, and executive stakeholders. - Proficiency in utilizing market data, customer insights, and campaign performance metrics to report on strategy effectiveness. - Experience in creating and executing go-to-market strategies for category-defining technology. - Direct experience managing and influencing distributed, global teams. - Demonstrated history of delivering thought leadership content, including white papers, executive narratives, and solution briefs for technical audiences. - Experience building and executing enablement programs for global sales organizations and channel partners. - Advanced degree (MBA or equivalent) in a relevant field. Benefits - Medical, dental, and vision insurance. - 401(k) plan with a Cisco matching contribution. - Paid parental leave. - Short and long-term disability coverage. - Basic life insurance. - 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees. - 1 paid day off for employee’s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco. - Non-exempt employees receive 16 days of paid vacation time per full calendar year. - Exempt employees participate in Cisco’s flexible vacation time off program. - 80 hours of sick time off provided on hire date and each January 1st thereafter. - Optional 10 paid days per full calendar year to volunteer.

• Lead the engineering team responsible for the day-to-day implementation, scaling, and operation of AI compute clusters. • Translate engineering roadmaps and technical requirements from the Director of AI Infrastructure into detailed project plans and execution milestones. • Drive delivery of cluster deployments, hardware bring-up, node configuration, and integration with orchestration and scheduling systems. • Ensure cluster reliability, uptime, and performance through monitoring, automation, and continuous operational improvements. • Oversee lifecycle operations for bare metal and GPU fleets, including provisioning, configuration management, firmware/driver updates, and hardware validation. • Manage incident response for GPU and cluster infrastructure, ensuring timely resolution and root-cause analysis. • Work closely with AI/ML, SRE, Networking, and Hardware Engineering teams to ensure cluster capabilities meet training and inference needs. • Coordinate with Product to confirm technical requirements, feature readiness, and delivery timelines. • Support integrations across networking, storage, scheduler, and resource orchestration components. • Improve tooling and automation for cluster provisioning, observability, configuration management, and large-scale fleet operations. • Contribute to the development and refinement of multi-tenant scheduling, workload management, and orchestration systems in partnership with senior technical staff. • Identify performance bottlenecks and propose engineering-level optimizations. • Coach and mentor engineers, fostering a high-performance, detail-oriented engineering culture. • Support career development, expectations, and performance management for team members. • Help refine engineering processes, including code reviews, testing standards, documentation, and operational runbooks.