DigitalOcean

Compensation

Full Description

About the position Responsibilities • Act as a trusted technical advisor for strategic accounts and partners, with a focus on AI/ML and GPU-based workloads. • Collaborate with Account Managers, Technical Account Managers, and Partners to develop success plans aligned to business goals. • Design, present, and implement scalable architectures, modernization strategies, and AI solutions tailored to customer needs. • Lead technical deep dives, workshops, proof-of-concepts, and executive briefings to accelerate adoption. • Demonstrate strong expertise in AI/ML frameworks like TensorFlow and PyTorch and usage of platforms like Hugging Face, with experience deploying and fine-tuning LLMs and GenAI models. • Optimize AI/ML workloads using tools like CUDA, TensorRT, vllm, and quantization methods (INT4, INT8, FP8). • Educate customers to build scalable AI applications like chatbots, inference services or recommendation systems using Kubernetes, NFS, and databases. • Demonstrate proficiency in DevOps tools like Docker, Terraform, and CI/CD pipelines. • Troubleshoot complex technical challenges in partnership with Engineering, Support, and Product teams. • Provide customer feedback to shape product roadmaps and enhance platform capabilities. • Support workload expansion, retention, and long-term partnership growth through proactive technical engagement. Requirements • 7+ years of Solutions Architecture, Technical Consulting, or Software Engineering experience, with a track record in pre-sales and solution strategy. • Deep expertise in AI/ML frameworks (TensorFlow, PyTorch) and platforms like Hugging Face. • Experience deploying and fine-tuning LLMs (DeepSeek, Llama, Claude, GPT-4) and GenAI models. • Strong knowledge of Kubernetes, Linux, distributed systems, NFS, Object Storage, and GPU optimization techniques (CUDA, TensorRT). • Hands-on experience leveraging vllm and various quantization methods (e.g., INT4, INT8, and FP8) for efficient model deployment. • Familiarity with DevOps tools (Docker, Terraform, CI/CD pipelines) and modern cloud-native practices. • Excellent communication skills, comfortable engaging and presenting to both engineers and executives. • Proven ability to lead complex technical engagements from discovery and solution design to post-deployment success. • Strong consultative approach, capable of identifying customer needs and crafting tailored cloud solutions that align 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 public cloud platforms (AWS, Azure, GCP), with experience designing solutions in multi-cloud or hybrid cloud architectures. • Advanced AI/ML and GPU certifications from major providers like NVIDIA and AMD. • Hands-on experience building internal tools, automation scripts, or frameworks that streamline cloud migrations, deployment workflows, or architectural best practices. • Active participation in cloud-native or developer communities, including presenting at meetups, conferences, or contributing to forums. • Published technical content such as blogs, whitepapers, solution guides, or documentation on cloud architecture, modernization strategies, or technical thought leadership. • Familiarity with partner ecosystems and integration strategies, working with ISVs, technology alliances, or channel partners to deliver joint solutions. Benefits • Competitive salary range of \$147,800 - \$184,750 based on market data, relevant years of experience, and skills. • Bonus eligibility based on company and individual performance. • Equity compensation including equity grants upon hire and participation in Employee Stock Purchase Program. • Reimbursement for relevant conferences, training, and education. • Access to LinkedIn Learning's 10,000+ courses for continued growth and development. • Flexible time off policy. • Employee Assistance Program and Local Employee Meetups.