I
Inetum
Data Engineer
AI/ML Data Engineer
On-siteMidData Engineerposted 4mo ago
Role summaryAI-generated
This role bridges data engineering and cybersecurity by designing scalable pipelines for security event processing, ensuring seamless integration with SOC/ITSM tools while optimizing incident response workflows with AI-driven automation. The ideal candidate will balance technical depth in data infrastructure with domain expertise in security operations to enhance production-grade AI/ML systems.
Skills required
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 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.
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