LLM Ops Engineer - Cloud Platform

Job Overview:

We are looking for a skilled LLM Ops Engineer with expertise in deploying and managing large language models (LLMs) across cloud environments. The ideal candidate will have experience with Infrastructure as Code (IaC), containerization, orchestration, and strong knowledge of cloud platforms. Additionally, the role will involve implementing monitoring, logging, and security best practices to ensure the efficient, secure, and scalable deployment of AI/LLM systems.

Required Skills & Qualifications :

- Proven experience with Infrastructure as Code (IaC) tools like Terraform or Ansible.

- Hands-on experience with containerization technologies such as Docker and orchestration using Kubernetes.

- In-depth knowledge of cloud platforms like AWS, Azure, or GCP, and experience in deploying/managing applications in cloud environments.

- Proficiency with monitoring tools like Prometheus, Grafana, and logging systems like the ELK stack for real-time performance tracking.

- Solid understanding of security best practices, particularly around sensitive data protection, content moderation, and performance implications in LLMs.

- Strong scripting skills using languages such as Python, Shell, or similar, with a focus on automation.

- Experience in managing large-scale AI/ML models or LLM deployments is highly desirable.

- Excellent problem-solving skills and the ability to troubleshoot and resolve issues in a distributed computing environment.

- Strong collaboration and communication skills to work in a cross-functional team environment.

Preferred Qualifications :

- Certifications in cloud platforms (e.g., AWS Certified Solutions Architect, Azure Administrator, GCP Professional Cloud Architect) are a plus.

- Previous experience working with large-scale LLM models such as GPT, BERT, or similar.

- Familiarity with LLM-specific tools and frameworks (e.g., Hugging Face, OpenAI APIs).