Senior Solutions Architect II, AI/ML

🕒 Abril 10

🗽 New York – Remoto

🗽 New York – Remote

💵 $150.000 - $186.000 / ano

⏰ Tempo Integral

🟠 Sênior

💻 Engenheiro de Soluções

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DigitalOcean

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 2011

☁️ SaaS

SaaS • Cloud Computing

A DigitalOcean é um provedor de infraestrutura em nuvem que oferece um conjunto de produtos e serviços para que desenvolvedores construam, implantem e dimensionem aplicações. Sua plataforma disponibiliza tutoriais abrangentes, materiais de referência e documentação de suporte para ajudar os usuários a gerenciar recursos de forma eficiente usando suas ferramentas de API e CLI. Com recursos como Droplets (máquinas virtuais), bancos de dados gerenciados, Kubernetes e um marketplace de aplicações de terceiros, a DigitalOcean prioriza simplicidade e desempenho. Atende tanto desenvolvedores individuais quanto organizações de maior porte que buscam soluções em nuvem fáceis de implementar e gerenciar.

Descrição

• Serve as a technical partner to Customer Success and Sales teams • Perform architecture reviews, proofs of concept, demos, and technical consultations • Uncover customer technical needs and demonstrate DigitalOcean's value proposition • Develop expertise in DigitalOcean's product portfolio, cloud landscape, and AI/ML platforms • Advocate for customers by providing product feedback, overcoming adoption blockers, and driving feature development • Provide personalized onboarding and resolve technical blockers throughout customers' cloud journeys • Design and review architectures for specific business use cases • Implement infrastructure management best practices to secure and optimize cloud resources • Identify cost reduction and performance improvement opportunities • Conduct customer workshops, training, and technical consultation sessions • Partner with Growth Account Managers and Customer Success Managers on retention and expansion success plans • Present product benefits, functionality, and technical solutions • Deploy and fine-tune LLMs and GenAI models; optimize GPU workloads using CUDA or TensorRT • Build scalable AI applications such as chatbots, inference services, and recommendation systems using Kubernetes and NFS • Design AI solutions, manage data pipelines, and integrate databases • Liaise with Engineering and Support to resolve escalations and growth obstacles • Drive process improvements and promote technical best practices • Contribute to internal and external documentation • Build tools to improve Premium Support customer experience and platform usability • Work independently and collaboratively with a global team

🎯 Requisitos

• Proven professional experience with cloud infrastructure, AI/ML platforms, or equivalent education • Expertise in AI/ML frameworks such as TensorFlow and PyTorch • Familiarity with platforms like Hugging Face • Experience deploying and fine-tuning LLMs and GenAI models • Deep knowledge of Linux, distributed systems, Kubernetes, NFS, Object Storage, and GPU optimization techniques such as CUDA and TensorRT • Hands-on experience with vllm and quantization methods such as INT4, INT8, and FP8 • Programming/development experience building AI-powered applications • Experience in a post-sales or technical consultant role focused on AI/ML and cloud solutions • Knowledge of provisioning, deployment strategies, Terraform, Kubernetes, and Docker • Track record of developing successful technical solutions, including AI/ML use cases • Strong understanding of AI/ML data pipelines, cloud-native databases, and integration strategies • Strong communication skills for explaining technical AI/ML concepts clearly and concisely • Fluency in English • Cloud certifications are highly desirable, including AWS, GCP, Oracle, or Azure • NVIDIA certifications around GPU and AI/ML • Networking certifications such as Cisco or Juniper • Programming/scripting knowledge in Ruby, Python, Go, or Bash • Source code experience with Git • Automation experience with Terraform, Ansible, Chef, Puppet, or Saltstack • Virtualization experience with KVM or Xen • Database experience with MongoDB, MySQL, Redis, or PostgreSQL • Open-source experience with CoreOS, Docker, Kubernetes, Vagrant, or related certifications • DigitalOcean API, libraries, and services experience • Linux certifications such as RHCSA/RHCE

🏖️ Benefícios

• Reimbursement for relevant conferences, training, and education • Access to LinkedIn Learning's 10,000+ courses • Employee Assistance Program • Local Employee Meetups • Flexible time off policy • Bonus eligibility based on company and individual performance • Equity compensation, including equity grants upon hire • Option to participate in the Employee Stock Purchase Program