About Us
At sofias, we are redefining how businesses adopt AI by creating intelligent agents that are ready to deploy and easy to integrate. Our mission is to make cutting-edge AI technology accessible to organizations of all sizes, enabling them to unlock new efficiencies and opportunities. As a growing startup, we are building the next generation of enterprise software for GenAI, and we want you to be part of this journey.
The Role
We are looking for an experienced DevOps engineer with a strong technical background and a passion for scalable infrastructure to join our team. This role is ideal for someone who thrives in dynamic environments, enjoys optimizing complex systems, and wants to work on technology that is shaping the future. You will play a pivotal role in ensuring our AI agent platform runs seamlessly and scales efficiently for our growing client base.
What You’ll Do
Container Orchestration : Design, deploy, and manage containerized applications using Docker and Kubernetes across multiple environments.
CI/CD Pipeline Development : Build and maintain robust continuous integration and deployment pipelines to ensure rapid, reliable software delivery.
Infrastructure Monitoring : Implement and maintain comprehensive telemetry and observability systems using Prometheus, Grafana, and related tools.
Data Pipeline Integration : Seamlessly integrate data pipelines and ML models with production applications, ensuring optimal performance and reliability.
Cloud Infrastructure : Manage and optimize cloud infrastructure to support our AI agents and client deployments.
System Reliability : Ensure high availability, performance, and security of our platform through proactive monitoring and incident response.
Automation : Develop infrastructure as code and automate operational processes to improve efficiency and reduce manual overhead.
Strategic Collaboration : Work directly with the founding team and engineering team to shape our technical infrastructure and deployment strategy .
What We’re Looking For
Must-Have Skills
Proven experience with container technologies (Docker, Kubernetes) in production environments.
Strong expertise in CI/CD pipeline design and implementation (Jenkins, GitLab CI, GitHub Actions, or similar).
Hands-on experience with monitoring and observability tools, particularly Prometheus and Grafana.
Demonstrated ability to integrate data pipelines and ML models with production applications.
Solid understanding of cloud platforms (AWS, GCP, or Azure).
Problem-solving mindset with the ability to troubleshoot complex distributed systems.
Excellent communication skills for cross-functional collaboration.
Nice-to-Have Skills
Experience with Infrastructure as Code tools (Terraform, Ansible, or similar).
Knowledge of service mesh technologies (Istio, Linkerd).
Familiarity with ML/AI model deployment and MLOps practices.
Understanding of security best practices and compliance requirements.
Experience working in startups or fast-paced agile environments.
Knowledge of log aggregation systems (ELK stack, Fluentd).
What We Offer
Competitive Salary : €45,000 gross annually.
Impactful Work : Be part of a growing startup where your infrastructure expertise directly enables our AI technology to scale.
Remote Flexibility : Work from the comfort of your home with a focus on results, not hours.
Professional Growth : Accelerate your career by working on cutting-edge AI technology.
Collaborative Environment : Join a team that values innovation, learning, and collaboration.
Strategic Involvement : Work closely with the founding team and have a say in the direction of the product and company.
Why Join Us?
If you're an experienced DevOps engineer looking to work on meaningful technology infrastructure, this is your opportunity to make an impact. At sofias, you'll be building the backbone that powers the next generation of AI agents, helping businesses unlock the potential of artificial intelligence. We value technical expertise, operational excellence, and a drive to build something extraordinary.
Ready to take the next step in your career? Let’s build the future of AI to