Job Description:

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).