AI DevOps Engineer (GCP)

Quick Facts

• Role: AI DevOps Engineer (GCP)

Description

Build and maintain AI infrastructure on GCP using Infrastructure as Code. Develop CI/CD and GitOps processes for AI platforms, AI agents, and RAG pipelines, while managing Kubernetes (GKE), Cloud Run, and containerized environments. Implement MLOps/LLMOps practices (monitoring, observability, evaluation, and deployment automation) and ensure security, scalability, and regulatory compliance (e.g., AI Act, DORA, GDPR) with supporting technical documentation.

Responsibilities

• Design and maintain AI infrastructure as Infrastructure as Code on GCP

• Build and evolve CI/CD and GitOps for AI platforms, AI agents, and RAG pipelines

• Manage Kubernetes environments (GKE), Cloud Run, and container solutions

• Implement MLOps and LLMOps practices, including monitoring, observability, evaluation, and deployment automation

• Build and maintain monitoring, logging, and cost reporting for AI and LLM service usage

• Ensure security, scalability, and regulatory compliance of AI environments (AI Act, DORA, GDPR)

• Prepare technical documentation

Requirements

• Higher education in Computer Science, Telecommunications, or related fields

• Minimum 3 years of experience in DevOps, MLOps, or Platform Engineering

• Practical knowledge of Google Cloud Platform: GKE, Cloud Run, IAM, VPC, Cloud Storage

• Experience with Terraform and a GitOps approach

• Very good knowledge of Docker and Kubernetes

• Experience building CI/CD pipelines

• Knowledge of Python, Bash, and YAML

• Knowledge of monitoring and observability (Prometheus, Grafana, OpenTelemetry or equivalent)

• Knowledge of security topics: IAM, secret management, and data encryption

• English proficiency at B2 or higher

Benefits

• B2B contract

• Hybrid model: 1 day per week working from the Warsaw office (Chmielna 89)

• Optional Luxmed and MyBenefit cafeteria package on preferential terms