Our client is a fast-growing AI technology company redefining how large-scale dynamic pricing is handled in real-time. The company is partnering with some of the world’s leading airlines to transform how pricing is done at scale. They've developed a cutting-edge platform that enables enterprise clients to move beyond manual pricing models and embrace a fully autonomous, AI-driven system that dynamically adjusts to real-time market conditions.

We are actively looking g for a DevOps Engineer to join the global team, and being a key member to monitor and maintaining the cloud-native infrastructure that supports highly scalable, AI-powered applications. You’ll work in a DevOps team responsible for deploying, monitoring, and automating systems across a Google Cloud Platform environment, collaborating closely with engineering teams working on advanced AI-powered projects.

This role is ideal for engineers who think about infrastructure from a reliability-first mindset and thrive in environments where experimentation, automation, and data-driven decision-making are embedded into the culture.

Responsibilities

Own availability and reliability of production services across GCP and Kubernetes.
Build and maintain infrastructure-as-code using Terraform and Helm (custom charts).
Design and improve monitoring and alerting systems using Prometheus, Grafana, and logging tools.
Collaborate with developers to enforce best practices in performance, observability, and deployment.
Improve deployment and rollback workflows via GitLab CI/CD and ArgoCD.
Write and maintain Python scripts and tools to automate operational tasks.
Contribute to incident management processes and on-call rotations.

Requirements

4+ years of experience in SRE, production engineering, or DevOps in high-availability systems.
2+ years working with Google Cloud Platform (GCP) in production environments.
2+ years of hands-on experience with Kubernetes (preferably managing multi-tenant clusters).
Strong experience with Terraform and Helm (preferably writing custom charts).
Proficiency in Python scripting for tooling, monitoring, or operational automation.
Experience with Prometheus, Grafana, and alerting best practices.

Advantages:

Experience managing GitOps with ArgoCD or similar tools.
Understanding of Kubernetes Operators and controller logic.
Python proficiency for coding beyond scripts (small services, integrations).
Familiarity with GCP services such as GKE, BigQuery, Dataflow, or VertexAI.

The company is committed to creating a diverse environment and is proud to be an equal-opportunity employer. They provide a collaborative working environment along with resources, and state-of-the-art tools & equipment to promote success; and a welcoming, inclusive corporate culture where individuals are recognized for their contributions.

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