Lead Cloud Solutions Architect

Remote - EuropeRemotelead

OtherSolutions ArchitectSoftware EngineeringCloud Solutions Architect

0 views0 saves0 applied

Key Responsibilities

Lead and mentor a team of Solutions Architects, fostering a culture of technical excellence, customer empathy, and collaborative execution.

Technical Tools

OtherSolutions ArchitectSoftware EngineeringCloud Solutions Architect

~1 min read

~1 min read

→Lead and mentor a team of Solutions Architects, fostering a culture of technical excellence, customer empathy, and collaborative execution.
→Oversee and participate in technical engagements including PoCs, workshops, architecture reviews, and trainings.
→Drive consistency and quality across infrastructure design, IaC practices, technical documentation, and customer enablement content.
→Collaborate closely with Product and Development teams, representing customer needs and helping shape the roadmap.
→Guide customers in optimizing ML/AI/HPC pipelines for performance, scalability, and cost-efficiency on Nebius cloud infrastructure.
→Build visibility and ownership culture amongst Solutions Architects.

5+ years of experience in a technical role (Solutions Architect, DevOps Engineer, ML Engineer, or similar) with a focus on cloud-native systems and distributed computing.
2+ years of experience leading or mentoring customer facing engineering teams.
Deep hands-on experience with Infrastructure as Code (Terraform, Ansible), Kubernetes, and cloud automation.
Strong communication and stakeholder management skills across both technical and non-technical audiences.
Passion for developing scalable, reliable cloud architectures and driving customer success.

~1 min read

Experience with HPC or ML orchestration frameworks (e.g., Slurm, Kubeflow, Ray).
Strong coding skills in Python and experience with GPU computing environments for ML/AI workloads.
Proficient in GPU stack components (e.g., CUDA, cuDNN) and cloud-native patterns for ML training/inference.
Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX).
Understanding of cloud-based ML tools and offerings from NVIDIA, AWS, Azure, or Google Cloud.
Experience participating in or leading technical contributions to conferences or open-source communities.