About the company:
KIEFER is building Greece's integrated AI ecosystem. From renewable energy infrastructure and AI systems to robotics and enterprise applications, we connect the technologies that power Europe's intelligent future. Founded in 2014, KIEFER has delivered 600MW+ of energy projects and is now developing sovereign AI infrastructure, enterprise AI products and physical AI systems for Greece and Southeast Europe.
Job Description
WHAT YOU WILL DO
Design, build, and scale automated CI/CD pipelines tailored for safe Over-The-Air (OTA) software and firmware rollouts to robots in the field.
Containerize and optimize complex AI workloads and ROS2 environments using Docker for deployment on edge hardware (NVIDIA Jetson platforms).
Configure and maintain lightweight container orchestration (K3s/Kubernetes) adapted for resource-constrained edge servers and local lab infrastructure.
Establish automated, resilient data-ingestion pipelines to stream high-density field data updates back to local servers.
Support the simulation infrastructure, ensuring a smooth automated data pipeline
WHAT YOU WILL NEED
3–5 years of hands-on DevOps/MLOps engineering experience within Linux-heavy environments.
Proven experience building automated deployment loops and handling container production environments (Docker, Kubernetes).
Familiarity with edge computing challenges, embedded hardware interfaces, or network data streaming protocols (MQTT, gRPC).
Strong scripting and automation capabilities (Python, Bash).
Fluency in both Greek and English
High autonomy and a problem-solving mindset — able to translate the infrastructure needs of diverse engineers into robust automated systems.
NICE TO HAVE
Direct experience with NVIDIA Jetson platforms
Background or strong personal interest in robotics systems or physical AI technologies.
WHAT IS THERE FOR YOU
Compensation: upper-quartile for the Greek market;
Ownership: Full accountability over the Robotics division's DevOps and Edge MLOps infrastructure — you define the automation standards;
Remote: Flexible format: fully remote, or hybrid from our Athens office;
AI-Native Environment: Real challenges across physical AI, edge servers, humanoid R&D, and advanced robotics deployment;
Growth: Possibility to get training from the Robotics companies;
Culture: Engineering-first, high autonomy, low bureaucracy — your infrastructure choices directly shape the fleet's execution capabilities.
