Description

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).

Education

Any Graduate