• Participarás en el diseño, desarrollo e implementación de soluciones de integración híbridas usando la plataforma Anypoint de Mulesoft • Colaborando en todas las fases del ciclo de vida del software: Evolución y diseño de arquitecturas basadas en APIs (HIP) • Análisis de requerimientos, diseño técnico y pruebas • Modelado y construcción de APIs REST y SOAP • Definición de arquitectura y gobernanza de APIs • Aseguramiento de estándares y buenas prácticas de diseño • Aplicación de mecanismos de autenticación y securización (OAuth 2.0, SAML, SSO, OpenID)

Role Description I’m building Interview Strategist™, an AI-powered career strategy platform built around the Interview Strategist Method™: Understand how hiring decisions are made. Stop being evaluated. Start influencing. The product concept, positioning, and go-to-market strategy are defined. I’m now looking for a Founding Engineer / Full-Stack Builder to take Interview Strategist™ from concept to a live, sellable SaaS platform. - Important upfront clarity - ❌ This is not a salaried role - ❌ This is not a funded company (yet) - ✅ This is a build-for-upside opportunity with EBITDA participation and exit upside If you enjoy building real products with real users—and sharing the upside—this may be for you. Interview Strategist™ is a web-based SaaS platform integrating LLM / ChatGPT-type models into structured, decision-driven user journeys. You will be responsible for designing and building: - A modern full-stack web application - Structured AI workflows (not just chat) - A clean, scalable, and well-documented architecture - A system that can be maintained or extended by others if needed Qualifications - Have already built and shipped web products - Are comfortable owning a system end-to-end - Understand (or are eager to master): - API-driven architectures - Prompt-based workflows - Cost / performance trade-offs with LLMs - Enjoy autonomy, speed, and responsibility Requirements - Frontend: React / Next.js (or equivalent modern framework) - Backend: Node.js or Python (FastAPI welcome) - Integration of OpenAI / LLM APIs into production workflows - User authentication, core flows, dashboards - Cloud deployment (AWS / GCP / Vercel or similar) - Version control, documentation, and basic DevOps hygiene - You don’t need to be an AI researcher—but you should be comfortable turning LLMs into real product logic, not just demos. Benefits - Participation in annual EBITDA (calculated on full-year results) - Participation in a future exit (if the platform is sold) - Full technical ownership of the build If this resonates, send me: - A short intro - What you’ve built before (GitHub, projects, products) - Your availability and motivation This is for someone who wants to build something real, learn fast, and share the upside.

• Implement and sustain cloud data platforms and industrial data solutions end‑to‑end • Collaborate with cross‑functional teams to meet customer outcomes and SLAs • Execute internal design, system build, and testing in support of solution road map • Develop and maintain documentation for pre/post‑implementation

• Design, implement, and tune high-fidelity detection rules across SIEM, EDR/XDR, and cloud-native SaaS platforms. • Work with centralized logging, data lakes, and detection telemetry. • Proactively analyze attacker tactics, techniques, and procedures (TTPs) and execute hypothesis-driven threat hunting campaigns. • Implement security automations using SOAR platforms and explore AI/ML and Large Language Models (LLMs) to enhance incident response and automated response actions. • Partner closely with SOC, Red Team, and Threat Intel to validate signal quality, reduce false positives, and improve MITRE ATT&CK coverage. • Provide technical guidance and mentorship to junior and mid-level security engineers.