13 дней назад
AI Cloud Security and Infrastructure Engineer (AI)
130 000 - 150 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Cloud Security and Infrastructure Engineer (AI): Designing and operating secure, scalable hybrid cloud environments and AI infrastructure for LLM-powered applications with an accent on cloud security, compliance, infrastructure-as-code, and containerized deployments. Focus on securing AI pipelines, managing Kubernetes and GPU/TPU resources, implementing observability and SIEM platforms, and leading incident response for security breaches and critical outages.
Location: Atlanta, United States; hybrid work
Hiring salary range: $130,000–$150,000 annually
Company
is a law firm focused on supporting clients through legal services while embracing inclusion and innovation.
What you will do
- Design, operate, and scale secure Azure, AWS, and GCP environments for AI workloads and data-intensive applications.
- Build and manage infrastructure-as-code using Terraform, Pulumi, and Azure ARM templates.
- Secure AI pipelines, CI/CD workflows, containerized LLM deployments, and end-to-end model lifecycles.
- Support fine-tuning, hosting, and scaling of LLMs using OpenAI, Hugging Face, and Azure OpenAI Service, including GPU/TPU resource management.
- Configure networking, DNS, SIEM, observability, threat detection, compliance reporting, and incident response capabilities.
- Assess infrastructure and data-pipeline risks, execute mitigation strategies, and communicate technical risks to executive stakeholders.
Requirements
- Bachelor’s degree or equivalent training, education, and experience.
- At least five years of cloud infrastructure engineering experience with a strong security focus.
- Hands-on experience with Kubernetes, Docker, infrastructure-as-code, AI/ML pipelines, and DevSecOps practices.
- Deep knowledge of PKI, encryption, cryptographic hashing, networking, DNS, and web-service security.
- Knowledge of ISO 27001, ISO 27701, ISO 42001, GDPR, CCPA, and CMMC Level 2 compliance frameworks.
- Experience with MLOps platforms such as MLflow and Kubeflow, and SIEM solutions such as Microsoft Sentinel.
Nice to have
- Certifications such as Azure Security Engineer Associate, CISSP, CCSP, CISM, or AIGP.
- Experience with prompt engineering and techniques for optimizing large language models.
Culture & Benefits
- Hybrid work environment.
- Focus on employee support, professional advancement, inclusion, and innovation.
- Work requiring strict confidentiality and responsible management of sensitive information.
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