• Design and implement highly scalable backend services, data pipelines, and integration endpoints that perform reliably at high volume. • Gather product and engineering requirements; write design documents and drive technical discussions to align cross-functional stakeholders. • Drive and lead the full software development lifecycle: product requirements, architecture, solution design, development, quality assurance, and maintenance. • Build systems with observability as a first-class concern proper monitoring, alerting, and dashboards so issues are caught before customers notice. • Mentor others on best practices and effectively share knowledge across the engineering team. • Communicate development progress clearly to product leads, engineering managers, and other stakeholders. • Be comfortable introducing new technologies and new ideas as required, including AI tools that accelerate your workflow and the team’s. • Navigate ambiguity and roadblocks proactively when a project hits a wall, you find a path forward and maintain cadence. • Work effectively as part of a large global team, attending scrum ceremonies, team events, and manager 1:1s. • Provide and respond to technical and behavioral feedback from managers and peers in written and verbal form.

• Desenvolver e evoluir aplicações full stack (back-end e front-end); • Construir e manter APIs REST e integrações com sistemas externos; • Implementar regras de negócio com foco em qualidade, performance e segurança; • Atuar no desenvolvimento e manutenção de interfaces web em Angular; • Apoiar na análise de requisitos funcionais e não funcionais; • Participar de definições técnicas, estimativas e decisões de implementação; • Colaborar com o time na sustentação e evolução contínua da plataforma.

• Design and implement scalable backend systems, focusing on performance, resilience, and maintainability. • Build and optimize data pipelines using Apache Spark and SQL to efficiently process large volumes of data. • Collaborate with data scientists to develop, refine, and deploy machine learning models in production environments. • Apply mathematical concepts such as statistical analysis, linear algebra, and optimization techniques to design algorithms, enhance data models, and evaluate system performance. • Work across multiple languages, including Scala, Python, and Java, to implement data-centric and AI-driven features. • Partner with cross-functional teams, including product managers and data scientists, to build innovative and impactful software solutions. • Participate in system architecture design, code reviews, mentoring, and continuous improvement of engineering practices.

• Tuning the performance of clusters and InfiniBand networks to ensure optimal operation in HPC and GPU-based environments. • Analyzing and troubleshooting the root cause of issues related to GPUs and InfiniBand networks, and proposing corrective actions. • Integrating new hardware into the existing infrastructure, including support for new GPU hardware through software stacks like Kubernetes, QEMU, and KVM. • Enhancing automation systems for proactive monitoring, detecting, and resolving issues in GPU and InfiniBand environments. • Configuring and managing GPU devices and InfiniBand fabrics, ensuring efficient and reliable operation.