Platform Engineer (Infrastructure & DevOps)

Company Description

Rokken is a software development company that provides customized technical solutions for clients. Our work combines machine learning, real-time 3D visualization, medical software, and AI-powered web applications.

Job Description

We are looking for a Platform Engineer to help design, deploy, and operate the infrastructure behind our AI and software products.

This role sits between infrastructure, DevOps, backend systems, and machine learning operations. You will help make our development and deployment environments reliable: CI/CD, worker machines, backend services, monitoring, secrets, backups, and developer workflows.

We are a small engineering team, so this is a high-ownership role. We need someone who can build practical systems, document them clearly, and work closely with ML engineers, backend developers, and project leads.

In This Role, You Will

• Design, deploy, and maintain infrastructure for AI and software products.
• Own CI/CD pipelines, self-hosted runners, deployment workflows, and release reliability.
• Operate backend services, worker services, databases, and supporting infrastructure.
• Improve observability through logs, metrics, dashboards, alerts, and incident investigation.
• Manage secrets, service accounts, network access, VPNs, and security-sensitive configuration.
• Support hybrid infrastructure: cloud or VPS services plus local or on-premise machines when needed.
• Help manage computational resources for ML training, batch processing, and AI workflows.
• Build and maintain backup, recovery, and maintenance procedures.
• Collaborate with ML and software engineers to make systems easier to deploy, debug, and scale.
• Document infrastructure decisions, operational procedures, and best practices.

Minimum Qualifications

• 3+ years of experience in infrastructure, platform engineering, DevOps, SRE, or a similar role.
• Strong Linux administration skills.
• Practical experience with Docker and containerized services.
• Ability to work with Kubernetes-based systems.
• Experience with CI/CD systems and Git-based development workflows.
• Ability to write scripts or small tools, preferably in Python or shell.
• Understanding of networking, security, secrets management, and service configuration.
• Experience operating production or production-like services.
• Strong problem-solving, documentation, and communication skills.

Preferred Qualifications

• Deeper experience with Kubernetes, Helm, GitOps, or other container orchestration and deployment workflows.
• Experience with GPU servers, ML workloads, or distributed computing.
• Experience with Python backend services, PostgreSQL, Redis, or similar systems.
• Familiarity with workflow orchestration systems.
• Experience with monitoring and logging stacks such as Grafana, Prometheus, Loki, Tempo, or similar tools.
• Experience with self-hosted GitHub runners or internal developer tooling.
• Experience with distributed or object storage such as Ceph, MinIO, JuiceFS, S3-compatible storage, or NAS systems.
• Experience with VPN or private-network tools.
• Experience with hybrid cloud and on-premise deployments.
• Backend development experience, especially around ML or data-processing workloads.

Working Style

This is not a pure IT support position and not a pure cloud administrator position. We are looking for someone who enjoys building practical infrastructure for real engineering teams: deploying services, making worker systems reliable, improving CI, debugging failures, and helping developers move faster without making systems fragile.

You do not need to be an expert in every tool listed above. We care more about strong fundamentals, good judgment, clear communication, and the ability to own systems over time.

We are an AI-forward engineering team, and we especially value people who already use modern AI agents in their daily development and operations work.

Trial Period

3 months.

Remote Work Policy

Regular collaboration with our Osaka and Sakai-based team is important for this role, especially during onboarding and early product delivery.

• Initial phase: on-site work preferred.
• After initial assessment: flexible work arrangements may be possible, depending on project needs and collaboration requirements.