Junior DevOps Engineer

• Minimum of 1 year of commercial experience in DevOps, Cloud, Platform Engineering - MUST HAVE!
• Good understanding of Linux, networking, and cloud infrastructure fundamentals.
• Practical knowledge of Kubernetes and Docker.
• Experience with CI/CD pipelines, preferably GitHub Actions, and familiarity with Git.
• Knowledge of at least one major cloud platform (AWS, GCP, or Azure) and an understanding of cloud infrastructure operations.
• Familiarity with Infrastructure as Code tools, such as Terraform, and HCL.
• Basic scripting skills in Bash or Python.
• Understanding of monitoring, application reliability, security, and troubleshooting in production environments.
• Willingness to learn, experiment, work independently, and take ownership of assigned infrastructure components.

Nice to Have:

• Hands-on experience with ArgoCD, GitOps workflows, Helm, and self-hosted infrastructure components.
• Experience with Prometheus and Grafana.
• Familiarity with PostgreSQL, Redis, Qdrant, JuiceFS, or similar data and infrastructure services.
• Knowledge of background job processing tools such as Celery and autoscaling solutions such as KEDA.
• Experience operating production Kubernetes clusters and designing or maintaining highly available applications.
• Familiarity with secrets management, cloud cost optimization, incident response, and SRE principles.
• Operational experience with multiple cloud platforms, including AWS, GCP, and Azure.

Hi there! If you’re looking for a high-impact position in an ambitious software house, we’ve got a match for you!

We are looking for an Engineer to work with our customer. Our client provides an AI-powered enterprise-grade platform that helps large organizations improve operational efficiency without losing control over their internal data.

The product acts as a secure layer on top of a company’s existing software (e.g. CRMs, communication tools, and document management systems) and serves three main purposes:

• Information Search: Enables employees to quickly find data scattered across different internal systems without having to move it.
• AI-Powered Insights: Analyzes company data and provides context-aware answers to support decision-making, while ensuring that confidential information is not exposed to public AI models.
• Process Automation: Reduces manual work and accelerates repetitive tasks across different departments (e.g. sales, finance, and operations).

The key differentiator is full data sovereignty and privacy. Companies do not need to migrate their databases or replace their existing tools. Instead, AI comes to the data wherever it currently resides, ensuring that sensitive business information remains fully protected.

You will be working with LLMs and many AI tools.

,[Build, maintain, and improve CI/CD pipelines for Node.js and Python applications using GitHub Actions., Operate and maintain Kubernetes environments across cloud platforms, including AWS and GCP., Manage GitOps-based deployments with ArgoCD and automate infrastructure provisioning using Infrastructure as Code., Monitor application performance, availability, and resource usage, helping identify and resolve production issues., Support application teams with deployments, scaling, troubleshooting, and reliability improvements., Contribute to infrastructure security, high availability, and operational best practices., Document infrastructure configurations, processes, and technical solutions.] Requirements: Kubernetes, GitHub Actions, Docker, Python, Linux, Git, ArgoCD, Prometheus, Grafana, PostgreSQL, Redis