Generative AI Operations Engineer (GenAI Ops)

About the role

We are looking for a highly motivated Generative AI Operations Engineer to join our innovative team. In this role you will build, deploy, and maintain the operational infrastructure for cutting‑edge generative AI models and multi‑agent systems across major cloud platforms.

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.
• Integrate AI agents with external tools and APIs using open standards such as the Model Context Protocol.
• Leverage AI‑powered development tools to accelerate the software development lifecycle.
• Define and manage infrastructure as code using Terraform, AWS CDK, CloudFormation or similar.
• Implement comprehensive monitoring, logging and tracing (e.g., OpenTelemetry) for models, agents and system health.
• Design scalable architectures for model serving and inference, optimizing performance and cost.
• Enforce security best practices and ensure compliance with industry regulations.

Required profile

• 3+ years of experience in DevOps, SRE or MLOps roles with a focus on cloud infrastructure.
• Strong background in AWS, GCP or Azure services.
• Proven ability to build and manage CI/CD pipelines using Jenkins, GitLab CI or cloud‑native solutions.
• Hands‑on experience deploying and operating LLM inference services (vLLM, Triton, TGI, Ray Serve, KServe/Seldon).

Required skills

• Python, Bash scripting
• Terraform, AWS CDK, CloudFormation
• Docker, Kubernetes
• Jenkins, GitLab CI
• OpenTelemetry or similar tracing tools
• Knowledge of Model Context Protocol (MCP)
• Experience with LLM inference platforms (vLLM, Triton, TGI, Ray Serve, KServe, Seldon)