10 years of experience in cloud architecture with 4 years with AI/ML solution design and implementation.
Deep hands-on expertise with AWS GCP an/or Azure services and tooling.
Strong experience with modern ML frameworks (TensorFlow PyTorch Hugging Face etc. and MLOps tools (Kubeflow MLflow Vertex AI Pipelines).
Proven record designing and deploying secure enterprise-grade cloud applications.
Solid understanding of cloud security data privacy and compliance standards.
Exceptional communication skills; able to influence and educate technical and non-technical audiences alike.
Demonstrated experience leading cross-functional teams and mentoring.
Familiarity with AI/ML-related security techniques such as model auditing explainability LLM endpoint protection and responsible AI frameworks.
What would be great to have:
Experience working with enterprise-scale financial services or other regulated industries.
Background in software engineering DevSecOps or AI security research.
Certifications: AWS Certified Machine Learning Specialty Google Cloud Professional ML Engineer or security-focused credentials (e.g. CISSP AWS Security Specialty).
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