Del Oro Consulting
Solutions Engineer
Remote Solutions Engineering role with clear candidate location fit.
PostedJun 15, 2026
Eligible countries1 accepted country
Seniority signalSenior
Work settingRemote
Accepted candidate locations
USA
Role overview
Solutions Engineer
Requirements and responsibilities
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Minimum Qualifications
- Seeking significant experience with end-to-end architecture/design work across multiple technology areas for DC and hybrid cloud solutions.
- Public, hybrid and private cloud computing and architecture experience along with Virtualization or X86 Architectures or Operating Systems
- Experienced in the design and/or deployment of Data Center solutions including traditional DC standalone design, VXLAN fabric-based architectures.
- Experience providing consumable documentation of standard methodologies for deployment around application acceleration, automation/management efficiencies, enterprise edge, and/or AI/ML solutions.
Preferred Qualifications
- 6+ years knowledge of any combination of Datacenter, Storage, Compute, Apps, Big Data, Converged Infrastructure, AI infrastructure or Data Center Networking experience
- Bachelor's Degree or equivalent in Computer Science, Computer Engineering, Electrical Engineering, or related field. Advanced degree is a plus.
- Experience working with partners to build and deliver GTM activities
- Knowledge and understanding of networking protocols and technologies.
- Excellent presentation skills - ability to deliver engaging workshops to both technical and non-technical audiences on AI topics
- AI experience with Nvidia, IBM, Microsoft, Dell, NetApp, HPE, and/or other AI vendors
- In-depth understanding of language models, including but not limited to GPT-3, BERT, or similar architectures.
- Expertise in training and fine-tuning LLMs using popular frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.
- Experience in deploying LLM models in cloud environments (e.g., AWS, Azure, GCP) and on-premises infrastructure.
- Familiarity with containerization technologies (e.g., Docker or equivalent experience) and orchestration tools (e.g., Kubernetes) for scalable and efficient model deployment.
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