Cloud Solutions Architect – Infra, AI Cloud
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Job Description
Cloud Solutions Architect providing advanced AI solutions and infrastructure for major clients. Leveraging GPU technologies and collaborating with cross-functional teams to deliver exceptional cloud services.
Responsibilities:
- Act as a trusted advisor to clients, providing technical expertise and guidance throughout engagements
- Conduct PoCs, workshops, presentations, and training sessions on GPU cloud technologies and best practices
- Collaborate with clients to understand their business requirements and develop solution architectures
- Design and document Infrastructure as Code solutions, technical documentation, and how-tos
- Help customers optimize pipeline performance and scalability
- Serve as a single point of expertise for customer scenarios across product, technical support, and marketing teams
- Assist with marketing efforts during events such as hackathons, conferences, and webinars
Requirements:
- 5+ years of experience as a cloud solutions architect, system/network engineer, developer, or similar technical role focused on cloud computing
- Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, and skills of writing code in Python
- Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL)
- Solid understanding of the cloud ML tools landscape from industry leaders
- Legal authorization to work in the U.S. on a full-time basis without visa sponsorship
Benefits:
- Comprehensive benefits package including 100% company-paid medical, dental, and vision coverage for employees and families
- 401(k) plan with a 4% match program
- Stock options plan
- Flexible remote work environment
- 20 weeks paid parental leave for primary caregivers, 12 weeks for secondary caregivers
- Up to $85/month for mobile and internet
- Opportunity to work with cutting-edge AI and cloud technologies
- Contribute to sustainable AI infrastructure with energy-efficient data centers
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