AI/ML Data Engineer

Job Description

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 quality
• Support the incident lifecycle (triage, investigation, and response) through AI-assisted models and automated playbooks
• Optimize response processes by reducing operational noise and improving incident prioritization
• Implement and evolve automation and orchestration workflows (SOAR)
• Ensure MLOps/AIOps practices, including versioning, performance monitoring, and drift detection
• Guarantee governance, security, and compliance in the use of data and AI models
• Mitigate 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 solutions
• Contribute to technical and strategic decision-making, including risk and ROI analysis

Qualifications

• Strong experience in Python (data engineering, automation, and integration)
• Solid knowledge of SQL / PostgreSQL
• Experience with data pipelines and log/event processing
• Knowledge of ML/Deep Learning frameworks (e.g., PyTorch, TensorFlow)
• Familiarity with versioning (Git), logging, and observability practices
• Knowledge of access control and authentication (SSO, SAML, LDAP)
• Experience or ability to work with data and ML infrastructure in production environments

Nice to Have:

• Experience with SIEM, SOAR, and EDR
• Experience with high-availability environments and infrastructure (including GPU)
• Knowledge of MLOps/AIOps and AI governance

Soft Skills:

• High level of autonomy and critical thinking
• Ability to work in complex, production-oriented environments
• Strong sense of ownership and attention to detail, especially in security contexts
• Good communication and collaboration skills with both technical and business teams
• Continuous improvement mindset and focus on operational efficiency

Additional Information

• Workplace type: Hybrid (max. of 3 times per week in the office).
• Location: Picoas, Lisboa.