Solutions Architect (Pre-Sales) (AI)

TL;DR

Solutions Architect (Pre-Sales) (AI Cloud Infrastructure): Serve as technical advisor for customers designing, deploying, and optimizing AI workloads on GPU cloud infrastructure with an accent on MLOps, scalable architectures, and performance optimization. Focus on leading PoCs, architectural workshops, and translating business requirements into Infrastructure as Code solutions.

Location: Legal authorization to work in the U.S. on a full-time basis without visa sponsorship. Flexible remote work environment.

Compensation: $225,000 – $315,000 OTE + equity, based on experience, skills, and location

Company

Fast-growing, publicly traded AI cloud infrastructure company with global R&D hubs in North America, Europe, and Israel, powering AI-driven businesses worldwide.

What you will do

• Serve as trusted technical advisor to customers throughout pre-sales and onboarding lifecycle.
• Lead PoCs, architectural workshops, presentations, and training on GPU cloud technologies.
• Collaborate with customers to understand requirements and design scalable solution architectures.
• Design and document IaC solutions, reference architectures, and technical guides.
• Optimize ML pipeline performance, throughput, and scalability for cloud resources.
• Bridge product, support, and marketing teams as cross-functional expert.
• Represent company at external events like hackathons and conferences.

Requirements

• Legal authorization to work in the U.S. on a full-time basis without visa sponsorship
• 5–10+ years as Cloud Solutions Architect, Systems/Network Engineer, Developer, or similar in cloud computing.
• Hands-on with IaC (Terraform/Ansible preferred), Kubernetes, and Python.
• Understanding of GPU computing for ML workloads, including GPU software stack (drivers, CUDA, OpenCL).
• Excellent communication skills for engineering and business audiences.
• Customer-centric mindset with track record of trusted advisor relationships.

Nice to have

• Experience with HPC/ML orchestration (Slurm, Kubeflow).
• Deep learning frameworks (TensorFlow, PyTorch).
• Familiarity with cloud ML tools (NVIDIA, AWS, Azure, Google).

Culture & Benefits

• 100% company-paid medical, dental, vision for employees and families.
• 401(k) with up to 4% match and immediate vesting.
• 20 weeks paid parental leave for primary caregivers; 12 weeks for secondary.
• Remote work reimbursement up to $85/month.
• Company-paid short/long-term disability and life insurance.
• Flexible remote work; culture of creativity, collaboration, and ownership.

Hiring process

• Level 1: Talent Acquisition (general fit, Q&A).
• Level 2: Hiring Manager (technical deep-dive).
• Level 3: Technical Assignment.
• Final: Leadership interview, references, background checks, offer.