About this role
We are looking for an AI/ML Data Engineer to join a team focused on transforming data and incident response processes into a robust, secure, and production-ready AI system. This role combines data engineering, automation, and cybersecurity, with a strong impact in a production environment.
Key Responsibilities:
Develop and operate data pipelines (ingestion, normalization, and enrichment) for security events (logs, alerts, and tickets)Implement end-to-end integrations with SOC and ITSM tools, ensuring data consistency and qualitySupport the incident lifecycle (triage, investigation, and response) through AI-assisted models and automated playbooksOptimize response processes by reducing operational noise and improving incident prioritizationImplement and evolve automation and orchestration workflows (SOAR)Ensure MLOps/AIOps practices, including versioning, performance monitoring, and drift detectionGuarantee governance, security, and compliance in the use of data and AI modelsMitigate risks associated with AI usage (e.g., prompt injection, data leakage, incorrect outputs)Collaborate with vendors and internal teams on the integration and operation of AI solutionsContribute to technical and strategic decision-making, including risk and ROI analysis Strong experience in Python (data engineering, automation, and integration)Solid knowledge of SQL / PostgreSQLExperience with data pipelines and log/event processingKnowledge of ML/Deep Learning frameworks (e.g., PyTorch, TensorFlow)Familiarity with versioning (Git), logging, and observability practicesKnowledge of access control and authentication (SSO, SAML, LDAP)Experience or ability to work with data and ML infrastructure in production environmentsNice to Have:
Experience with SIEM, SOAR, and EDRExperience with high-availability environments and infrastructure (including GPU)Knowledge of MLOps/AIOps and AI governanceSoft Skills:
High level of autonomy and critical thinkingAbility to work in complex, production-oriented environmentsStrong sense of ownership and attention to detail, especially in security contextsGood communication and collaboration skills with both technical and business teamsContinuous improvement mindset and focus on operational efficiency Workplace type: Hybrid (max. of 3 times per week in the office).Location: Picoas, Lisboa.