Senior Solutions Architect II, AI/ML

DigitalOceanSan Francisco, CA
$150,000 - $182,000Remote

About The Position

DigitalOcean is seeking a Senior Solutions Architect II with expertise in AI/ML to join their team. This role focuses on supporting the success and retention of high-value customers by acting as a technical subject matter expert on DigitalOcean's portfolio. The Solutions Architect will collaborate with Customer Success, Sales, and Support teams to retain and grow the largest customers, advise on best practices, and guide customers to optimal solutions. The role also involves working with Product, Engineering, and Operations to ensure customer needs and market insights are fed back into product development. This is a growth opportunity for a motivated individual to expand DigitalOcean's presence in the region, requiring technical depth, excellent communication skills, and a self-starter mentality.

Requirements

  • Proven professional experience with cloud infrastructure, AI/ML platforms, or equivalent education.
  • Expertise in AI/ML frameworks (e.g., TensorFlow, PyTorch) and familiarity with platforms like Hugging Face.
  • Experience deploying and fine-tuning LLMs (e.g., DeepSeek, Llama, Claude, GPT-4) and GenAI models.
  • Deep knowledge of Linux, distributed systems, Kubernetes, NFS, Object Storage, and GPU optimization techniques (e.g., CUDA, TensorRT).
  • Hands-on experience leveraging vllm and various quantization methods (e.g., INT4, INT8, and FP8) for efficient model deployment.
  • Programming/development experience, particularly in building AI-powered applications (e.g., recommendation systems, chatbots).
  • Experience working in a post-sales or technical consultant role with a focus on AI/ML and cloud solutions.
  • Knowledge of provisioning, deployment strategies, and tools like Terraform, Kubernetes, and Docker.
  • Passionate about customer experience and leveraging AI/ML to solve complex business problems.
  • Track record of developing successful technical solutions, including AI/ML use cases, to address customer challenges.
  • Ability to balance the demands of multiple stakeholders, define priorities, and set appropriate expectations.
  • Strong understanding of AI/ML data pipelines, cloud-native databases, and integration strategies.
  • Passionate about technology, open source projects, and applying cutting-edge AI/ML innovations.
  • Strong communication skills, with the ability to explain technical AI/ML concepts in clear and concise terms.
  • Quickly learn DigitalOcean systems and adapt to rapid changes in cloud and AI/ML trends.
  • Fluency in English.
  • Highly motivated with a self-starter mentality, ready to tackle AI/ML challenges head-on.

Nice To Haves

  • Cloud certifications (AWS/GCP/Oracle/Azure)
  • NVIDIA Certifications around GPU and AI/ML
  • Networking: Cisco/Juniper Certifications
  • Programming/Scripting: Ruby, Python, Go, Bash
  • Source Code: Git
  • Automation: Terraform, Ansible, Chef, Puppet, Saltstack
  • Virtualization: KVM, Xen
  • Databases: MongoDB, MySQL, Redis, PostgreSQL
  • Open Source: CoreOS, Docker, Kubernetes (CKA/CKE), Vagrant
  • DigitalOcean: API, libraries, services
  • Linux: RHCSA/RHCE

Responsibilities

  • Serve as a technical partner to the success and sales teams, performing architecture reviews, proof of concepts, and demos.
  • Uncover customer technical needs and demonstrate DigitalOcean's value proposition.
  • Collaborate with Account Executives, Global Account Managers, and Technical Account Managers to retain large customers and expand their workloads on DigitalOcean.
  • Develop deep expertise in the DigitalOcean product portfolio, the evolving cloud landscape, and AI/ML platforms.
  • Advocate for customers by providing feedback to product teams, overcoming adoption blockers, and driving new feature development.
  • Offer personalized onboarding assistance and guide customers through their cloud journey, resolving technical blockers.
  • Design and review architecture tailored to specific business use cases, ensuring optimal solutions for customers.
  • Implement and oversee infrastructure management best practices to secure and optimize cloud resources.
  • Identify opportunities for cost reduction and performance improvement, helping customers make data-driven cloud optimization decisions.
  • Conduct technical consultation sessions, workshops, and training for customers.
  • Partner with Growth Account Managers and Customer Success Managers to create success plans for customer retention, expansion, and satisfaction.
  • Provide regular presentations articulating product benefits, functionality, and technical solutions.
  • 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 GPU workloads using CUDA or TensorRT and build scalable AI applications like chatbots, inference services or recommendation systems using Kubernetes and NFS.
  • Design AI solutions tailored to business needs, manage data pipelines, and integrate databases.
  • Liaise with Engineering and Support teams to resolve escalations and growth obstacles.
  • Identify and drive process improvement opportunities and promote technical best practices across the organization.
  • Contribute to internal and external documentation, such as "The Navigator’s Guide to DO."
  • Build tools to enhance the experience of Premium Support customers and improve platform usability.
  • Demonstrate proficiency in DevOps tools like Docker, Terraform, and CI/CD pipelines.
  • Leverage expertise in Kubernetes, Managed DBaaS, and the DigitalOcean GenAI Platform.
  • Work both independently and collaboratively with a global team of Solutions Architects, Customer Success Managers, and Account Managers.

Benefits

  • Competitive array of 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
  • Bonus in addition to base salary
  • Equity compensation
  • Employee Stock Purchase Program
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