Sólides

• Provide strategic consulting to Product and Business teams, translating requirements and mapping technical and functional challenges • Design system architectures with a focus on scalability and resilience, prioritizing cloud ecosystems (AWS/GCP) • Select the most effective technologies, frameworks, and integration patterns for each solution • Ensure architectural alignment with DevOps principles, including Infrastructure as Code, CI/CD, and full automation • Maintain and produce comprehensive technical documentation (RFCs, flows, and diagrams) to guide technical development • Lead PoCs and evaluate market innovations to drive continuous evolution of our technology platform • Collaborate with engineering teams during implementation, safeguarding the integrity of the original solution design • Monitor security and performance and apply cost governance (FinOps) across all proposed architectures

• Establish and automate CI/CD pipelines for the agile release of AI/ML systems and mission-critical applications • Ensure high availability, observability, and ongoing support of critical production systems • Lead cost governance (FinOps), monitoring consumption and implementing financial optimization tactics • Manage and continuously evolve our cloud infrastructure (AWS/GCP), pursuing state-of-the-art solutions • Develop architectural improvements to support GenAI demands, focusing on low latency and scalability • Work closely with Data Scientists to improve the model lifecycle through MLOps practices • Create guardrails and automations to detect financial anomalies and reduce resource waste.

• Lead the end-to-end data science project lifecycle, from understanding the business pain point to deploying and monitoring models in production • Develop and enhance Machine Learning models (supervised and unsupervised) applied to recruitment, selection, retention, and engagement • Perform advanced exploratory analyses to identify patterns and hidden opportunities in user behavior • Collaborate closely with Product and Engineering teams to integrate data solutions directly into the platform • Ensure model quality and governance, focusing on bias mitigation and explainability (XAI) • Mentor junior team members, promoting the dissemination of best practices in coding, experimentation, and scientific rigor • Communicate technical findings clearly and strategically to stakeholders across different areas of the company.