Senior Solutions Architect II (AI/ML)

DigitalOcean • San Francisco, CA

1d • $100,000 - $160,000 • Remote

About The Position

DigitalOcean is seeking a Senior Solutions Architect II to help strategic accounts and partners solve complex cloud infrastructure challenges, with an emphasis on AI/ML and GPU-based workloads. Reporting to the Senior Manager of Solutions Architecture, this role partners with customers and internal account teams to design, implement, and optimize scalable, reliable cloud solutions. The position influences technical and business decisions, supports workload modernization, and helps position DigitalOcean as a preferred cloud provider for AI/ML and GPU needs.

The role collaborates with Sales, Technical Account Management, partners, Product, Engineering, and Operations. As a technical subject matter expert and trusted advisor, the Senior Solutions Architect guides customers through cloud adoption, cloud-native solution design, and legacy modernization. The role also leads technical engagements from discovery through implementation and post-deployment success, and shares customer feedback to inform product and platform improvements.

This is a remote role. Compensation is listed as a base salary range of $100,000–$120,000 and on-target earnings of $133,333–$160,000. The role is eligible for the annual bonus plan, and may be eligible for a new-hire equity grant, subject to plan terms and local eligibility. Benefits and eligibility vary by location; offerings may include flexible time off, mental health and well-being support, and reimbursement for relevant conferences, training, and education.

Requirements

• At least 7 years of experience in Solutions Architecture, Technical Consulting, or Software Engineering, with a track record in pre-sales and solution strategy.
• Deep expertise in AI/ML frameworks such as TensorFlow and PyTorch and platforms such as Hugging Face.
• Experience deploying and fine-tuning LLMs and other generative AI models using SFT, LoRA, and QLoRA techniques.
• Strong knowledge of Kubernetes, Linux, distributed systems, NFS, object storage, and GPU software ecosystems such as CUDA and ROCm.
• Hands-on experience with vLLM, SGLang, TensorRT, and quantization methods such as INT4, INT8, and FP8.
• Familiarity with Docker, Terraform, CI/CD pipelines, and modern cloud-native practices.
• Excellent communication skills, including the ability to engage and present to engineers and executives.
• Proven ability to lead complex technical engagements from discovery and solution design to post-deployment success.
• Strong consultative approach and ability to identify customer needs and develop tailored cloud solutions aligned with business objectives.

Nice To Haves

• Contributions to open-source or technical communities related to AI/ML, cloud infrastructure, DevOps, or cloud-native technologies.
• Advanced knowledge of AWS, Azure, or GCP, with experience designing multi-cloud or hybrid-cloud architectures.
• Advanced AI/ML and GPU certifications from providers such as NVIDIA or AMD.
• Hands-on experience building internal tools, automation scripts, or frameworks for cloud migrations, deployment workflows, or architectural best practices.
• Participation in cloud-native or developer communities, including presenting at meetups or conferences or contributing to forums.
• Published technical content such as blogs, whitepapers, solution guides, or documentation on cloud architecture, modernization, or technical thought leadership.
• Familiarity with partner ecosystems and integration strategies, including work with ISVs, technology alliances, or channel partners.

Responsibilities

• Act as a trusted technical advisor to strategic accounts and partners, focusing on AI/ML and GPU-based workloads.
• Collaborate with Account Executives, Technical Account Managers, and partners to develop success plans aligned with business goals.
• Design, present, and implement scalable architectures, modernization strategies, and AI solutions tailored to customer needs.
• Lead technical deep dives, workshops, proofs of concept, and executive briefings to accelerate adoption.
• Advise customers on deploying and fine-tuning LLMs and generative AI models, and optimizing workloads with inference engines and quantization methods.
• Educate customers on building scalable AI applications, such as chatbots, inference services, and recommendation systems, using Kubernetes, NFS, and databases.
• Troubleshoot complex technical challenges with Engineering, Support, and Product teams.
• Provide customer feedback to inform product roadmaps and improve platform capabilities.
• Support workload expansion, retention, and long-term partnership growth through proactive technical engagement.
• Lead complex technical engagements from discovery and solution design through post-deployment success.

Benefits

• Annual bonus plan eligibility; bonus amounts depend on company and individual performance.
• May be eligible for a new-hire equity grant, subject to plan terms and local eligibility.
• Employee Stock Purchase Program opportunity in participating countries, subject to applicable plan terms.
• Reimbursement for relevant conferences, training, and education, subject to company policy.
• Flexible time off may be available, depending on location and eligibility.
• Mental health and well-being support may be available, depending on location and eligibility.
• Local team meetups may be offered, depending on location and eligibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed