Solution Architect AI infrastructure & Private Cloud at Sofia, Bulgaria

Job Description:

Required Skills:

1. HPC & AI Infrastructure

· Extensive knowledge of HPC technologies and workload scheduler such as Slurm and/or Altair PBS Pro,

· Proficient in HPC cluster management tools, including HPE Cluster Management (HPCM) and/or NVIDIA Base Command Manager.

· Experience with HPC cluster managers like HPE Cluster Management (HPCM) and/or NVIDIA Base Command Manager.

· Good understanding with high-speed networking stacks (InfiniBand, Mellanox) and performance tuning of HPC components.

· Solid grasp of high-speed networking technologies, such as InfiniBand and Ethernet.

2. Containerization & Orchestration

· Extensive hands-on experience with containerization technologies such as Docker, Podman, and Singularity

· Proficiency with at least two container orchestration platforms: CNCF Kubernetes, Red Hat OpenShift, SUSE Rancher (RKE/K3S), Canonical Charmed Kubernetes.

· Strong understanding of GPU technologies, including the NVIDIA GPU Operator for Kubernetes-based environments and DCGM (Data Center GPU Manager) for GPU health and performance monitoring.

3.Operating Systems & Virtualization

· Extensive experience in Linux system administration, including package management, boot process troubleshooting, performance tuning, and network configuration.

· Proficient with multiple Linux distributions, with hands-on expertise in at least two of the following: RHEL, SLES, and Ubuntu.

· Experience with virtualization technologies, including KVM and OpenShift Virtualization, for deploying and managing virtualized workloads in hybrid cloud environments.

4. Cloud, DevOps & MLOps

· Solid understanding of hybrid cloud architectures and experience working with major cloud platforms in conjunction with on-premises infrastructure.

· Familiarity with DevOps practices, including CI/CD pipelines, infrastructure as code (IaC), and microservices-based application delivery.

· Experience integrating and operationalizing open-source AI/ML tools and frameworks, supporting the full model lifecycle from development to deployment.

· Good understanding of cloud-native security, observability, and compliance frameworks, ensuring secure and reliable AI/ML operations at scale.

5. Networking & Protocols

· Strong understanding of core networking principles, including DNS, TCP/IP, routing, and load balancing, essential for designing resilient and scalable infrastructure.

· Working knowledge of key network protocols, such as S3, NFS, and SMB/CIFS, for data access, transfer, and integration across hybrid environments.

6. Programming & Automation

· Proficiency in scripting or programming languages such as Python and Bash.

· Experience automating infrastructure and AI workflows.

7. Soft Skills & Leadership

· Excellent problem-solving, analytical thinking, and communication skills for engaging both technical and non-technical stakeholders.

· Proven ability to lead complex technical projects from requirements gathering through architecture, design, and delivery.

· Strong business acumen with the ability to align technical solutions with client challenges and objectives.

Qualifications:

· Bachelor’s/master’s degree in computer science, Information Technology, or a related field.

· Professional certifications in AI Infrastructure, Containers and Kubernetes are highly desirable —such as RHCSA, RHCE, CNCF certifications (CKA, CKAD, CKS), NVIDIA-Certified Associate - AI Infrastructure and Operations

· Typically, 8–10 years of hands-on experience in architecting and implementing HPC, AI/ML, and container platform solutions within hybrid or private cloud environments, with a strong focus on scalability, performance, and enterprise integration.