Own the technical relationship with DigitalOcean’s highest-value customers, including Fortune 500 companies and global technology leaders.
Serve as the trusted technical advisor and executive-facing point of contact, building deep, lasting relationships with VP- and SVP-level stakeholders.
Drive regular technical and strategic alignment sessions (QBRs, EBRs), proactively shaping the customer’s roadmap to maximize the value of DigitalOcean infrastructure.
Engage with C-level and VP-level contacts with confidence, clarity, and authority.
Deliver high-impact, boardroom-ready presentations on architecture decisions, cost-performance tradeoffs, and innovation opportunities.
Navigate complex org structures, ensuring DigitalOcean maintains executive alignment and account control at every level.
Provide expert guidance on designing and scaling AI/ML, containerized, and GPU-intensive workloads on DigitalOcean.
Assist customers with architectural planning, workload migration, performance tuning, and incident response.
Collaborate directly with engineering and product teams to address customer roadblocks and influence the product roadmap based on enterprise needs.
Own technical success across a portfolio of DigitalOcean’s largest and most strategic accounts.
Identify opportunities for workload expansion, cost optimization, and operational efficiency.
Act as the voice of the customer, providing structured feedback to influence DigitalOcean's offerings and go-to-market strategies.

Requirements

7+ years supporting enterprise or strategic accounts in a customer-facing technical role (TAM, Solutions Architect, or equivalent).
Experience working with large-scale organizations like AMD, Intel, or similar, including managing executive-level relationships and navigating matrixed stakeholders.
Deep understanding of cloud architecture for AI/ML, including GPU orchestration, inference/training pipelines, and model deployment.
Proficient in at least one major cloud platform (AWS, GCP, Azure) and familiar with DigitalOcean or other developer-focused platforms.
Strong hands-on skills with Linux systems, networking, containers (Docker/Kubernetes), and automation (Terraform, Ansible).
Programming/scripting in Python, Go, or similar—especially relevant to AI/ML and MLOps use cases.
Understanding of AI/ML infrastructure stacks: PyTorch, TensorFlow, ONNX, Hugging Face, NVIDIA Triton, etc.
Comfort with modern DevOps and data stack tools (CI/CD, GitOps, observability, pipelines).

Benefits

Employee Assistance Program
Local Employee Meetups
Flexible time off policy
Reimbursement for relevant conferences, training, and education
Access to LinkedIn Learning's 10,000+ courses
Competitive array of benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

cloud architectureAI/MLGPU orchestrationinference pipelinesmodel deploymentLinux systemsnetworkingcontainersprogramming in Pythonprogramming in Go

Soft Skills

relationship buildingtechnical advisoryexecutive communicationpresentation skillsstrategic alignmentcustomer advocacyinfluencingcollaborationproblem-solvingnavigating complex structures