Generative AI Operations Engineer (GenAI Ops)

About the role

We are looking for a Generative AI Operations Engineer to design, deploy and maintain the infrastructure that powers our large‑scale generative AI models and multi‑agent systems. The role works closely with data scientists, machine‑learning engineers and software developers to ensure the services are scalable, reliable and cost‑effective across major cloud platforms. This is a fully remote position based in Armenia.

Key responsibilities

• Design, implement and maintain automated CI/CD pipelines for training, evaluating and deploying large language models and AI agents.
• Orchestrate sophisticated multi‑agent workflows, ensuring seamless agent‑to‑agent communication and collaboration.
• Integrate AI agents with external tools and APIs using open standards such as the Model Context Protocol (MCP).
• Utilize AI‑powered development tools to accelerate infrastructure coding, testing and troubleshooting.
• Define and manage infrastructure as code (IaC) using cloud‑native services or tools like Terraform.
• Implement comprehensive monitoring, logging and observability for models, agents and system health.
• Design scalable architectures for model serving and inference, continuously optimizing performance and cost.
• Enforce security best practices and ensure compliance with relevant industry standards.

Required profile

• Minimum 3 years of experience in DevOps, SRE or MLOps roles with a focus on cloud infrastructure.
• Strong background in major cloud platforms (AWS, GCP, Azure).
• Proven ability to build and manage CI/CD pipelines.
• Experience with infrastructure‑as‑code and container orchestration technologies.
• Proficiency in scripting languages such as Python or Bash.

Required skills

• Python
• Bash
• Jenkins
• GitLab CI
• AWS
• Google Cloud Platform (GCP)
• Microsoft Azure
• Terraform
• AWS CDK
• AWS CloudFormation
• Docker
• Kubernetes
• Model Context Protocol (MCP)