Key Customers Solutions Architect
Germany. Fully remote or flexible working arrangements within Europe.Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5 to 10+ years of experience
- Required Skills
- AWSProject ManagementPythonGCPKubeflowKubernetesPyTorchAzureTensorflowProblem SolvingTerraformTroubleshootingStakeholder managementAnsible
Requirements
- 5 to 10+ years of experience in roles such as Solutions Architect, Customer Engineer, Technical Account Manager, or similar cloud-focused technical positions.
- Strong hands-on experience with cloud infrastructure, AI/ML workloads, and large-scale GPU environments.
- Expertise with Infrastructure as Code tools such as Terraform and Ansible.
- Practical experience with Kubernetes and Python programming.
- Strong understanding of GPU computing technologies, including ML training, inference workloads, CUDA, and related GPU stacks.
- Excellent troubleshooting and problem-solving skills in complex technical environments.
- Ability to communicate advanced technical concepts clearly to both technical and non-technical stakeholders.
- Proven customer-facing experience with the ability to build trust and maintain strong long-term client relationships.
- Experience with HPC or ML orchestration frameworks such as Slurm or Kubeflow is considered an advantage.
- Familiarity with deep learning frameworks including PyTorch or TensorFlow is a plus.
- Knowledge of AI and ML tooling across cloud providers such as AWS, Azure, Google Cloud, or NVIDIA ecosystems is beneficial.
- Strong project management, prioritization, and stakeholder management capabilities.
- Experience mentoring technical teams or contributing to collaborative technical leadership initiatives is valued.
Responsibilities
- Serve as the primary technical advisor and point of contact for strategic customers using large-scale GPU cloud infrastructure.
- Support customers in designing, deploying, troubleshooting, and scaling AI/ML solutions and workloads.
- Optimize GPU performance for machine learning training and inference tasks, ensuring high efficiency and scalability.
- Guide customers through infrastructure integration and cloud architecture best practices.
- Collaborate closely with sales teams to support customer engagements, identify growth opportunities, and deliver technical presentations or demonstrations.
- Act as a liaison between customers and internal product or engineering teams by communicating feature requests, feedback, and technical requirements.
- Troubleshoot complex technical issues related to AI/ML workloads, Kubernetes environments, GPU infrastructure, and cloud services.
- Build long-term trusted relationships with customers by providing proactive technical guidance and strategic recommendations.
- Participate in cross-functional initiatives to improve customer experience, technical processes, and service delivery.
- Support internal knowledge sharing, technical mentoring, and collaborative problem-solving activities.
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