Senior DevOps Engineer

Protex AI Ltd.

Job Overview

Location

Hungary

Job Type

Full-time

Full Job Description

📋 Description

• Senior DevOps Engineer role focused on building and maintaining scalable infrastructure for AI-powered safety systems used by global industry leaders.
• Day-to-day responsibilities include implementing CI/CD pipelines, designing observability systems, ensuring system reliability across cloud and edge environments, maintaining environment parity (Dev, Stage, Prod), and supporting secure, high-quality data deployment globally.
• The Infrastructure Team at Protex AI provides the foundational systems that enable real-time computer vision applications and proactive workplace safety at scale, supporting deployments in 20+ countries for clients like DHL, Amazon, and Tesla.
• In this role, you will gain deep expertise in cloud-native infrastructure, observability, compliance-driven deployments (including GDPR), and cross-functional collaboration with engineering teams to improve developer experience and system reliability.

🎯 Requirements

• 5+ years of professional experience in DevOps, Infrastructure, or SRE roles
• Expertise in monitoring, observability, and reliability best practices
• Hands-on experience with Kubernetes, Terraform, ECS
• Solid knowledge of AWS services (e.g., Lambda, EC2, S3, CloudWatch)
• Ability to deploy infrastructure across regions while maintaining GDPR and other compliance standards
• Bachelor’s degree in Computer Science or a related field

🏖️ Benefits

• Opportunity to work on cutting-edge AI-driven safety problems with global impact
• Ownership, autonomy, and the ability to make a tangible impact on workplace safety worldwide
• Inclusive and equitable workplace committed to diversity and equal opportunity

Skills & Technologies

AWS

Kubernetes

Terraform

DevOps

Senior

Onsite

Degree Required

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Protex AI Ltd.

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About Protex AI Ltd.

Protex AI develops computer-vision software that plugs into existing CCTV networks to detect unsafe behaviours and near-miss events in industrial workplaces in real time. The cloud platform uses machine-learning models to flag non-compliance with PPE, vehicle-pedestrian proximity, blocked exits and ergonomic risks, sending alerts to EHS teams to prevent injuries. Dashboard analytics quantify safety trends, benchmark sites and guide targeted interventions, helping large manufacturers, logistics and construction companies reduce incidents, insurance costs and operational downtime while automating routine audits.

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