AI/ML Data Engineer

Inetum is a European leader in digital services. Inetum’s team of 28,000 consultants and specialists strive every day to make a digital impact for businesses, public sector entities and society. Inetum’s solutions aim at contributing to its clients’ performance and innovation as well as the common good.  

Present in 19 countries with a dense network of sites, Inetum partners with major software publishers to meet the challenges of digital transformation with proximity and flexibility.  

Driven by its ambition for growth and scale, Inetum generated sales of 2.5 billion euros in 2023.  

We are looking for anAI/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 operatedata pipelines (ingestion, normalization, and enrichment) for security events (logs, alerts, and tickets)
• Implement end-to-end integrations withSOC and ITSM tools, ensuring data consistency and quality
• Support the incident lifecycle (triage, investigation, and response) throughAI-assisted models and automated playbooks
• Optimize response processes by reducing operational noise and improving incident prioritization
• Implement and evolveautomation and orchestration workflows (SOAR)
• EnsureMLOps/AIOps practices, including versioning, performance monitoring, and drift detection
• Guaranteegovernance, 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, includingrisk and ROI analysis

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

Nice to Have:

• Experience withSIEM, SOAR, and EDR
• Experience withhigh-availability environments and infrastructure (including GPU)
• Knowledge ofMLOps/AIOps and AI governance

Soft Skills:

• High level ofautonomy and critical thinking
• Ability to work incomplex, production-oriented environments
• Strong sense ofownership 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

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