Senior Security for AI Engineer
- Design and implement secure AI architectures, covering ML security, data protection, model robustness, adversarial resilience and prevention of AI misuse.
- Integrate security and governance controls into MLOps pipelines, strengthening MlSecOps practices and ensuring compliance throughout the model lifecycle.
- Lead AI validation and assurance activities, including robustness testing, bias and drift detection, anomaly identification, and evidence preparation for audits.
- Translate regulatory and standards requirements (EU AI Act, ISO/IEC 42001, AIGA) into actionable engineering and governance controls within client and internal projects.
- Act as technical authority for Security for AI initiatives during design, development, validation, deployment and monitoring phases.
- Define and operationalize AI Governance frameworks involving risk classification, impact assessments, documentation, traceability and lifecycle control gates.
- Coordinate multidisciplinary teams composed of AI engineers, software developers, cloud specialists and security experts.
- Serve as primary point of contact for clients and business stakeholders, ensuring alignment between security, compliance and business value.
- Support pre‑sales activities through proposal inputs, solution design and client presentations related to AI Security.
- Apply hands‑on knowledge in NLP, anomaly and attack detection, optimization techniques, and secure AI development and validation.
- Utilize advanced AI frameworks such as PyTorch, TensorFlow, HuggingFace and scikit‑learn in secure‑by‑design engineering workflows.
- Ensure compliance with emerging AI security standards and maintain audit‑ready processes across the full AI lifecycle.
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