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The application window is expected to close on March 7, 2025
Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.
We are seeking a Solutions Engineer to join our dynamic sales team. As an SE, you will drive the adoption of our Data Center networking, Compute and AI solutions across various industries. You will identify potential clients, understand their specific needs, and provide tailored solutions that enhance their business operations. This role requires a deep understanding of Data Center Compute & Networking.
As a Cloud and AI Infrastructure Solutions Engineer, you will play a pivotal role in facilitating the success of the Cisco Field Sales teams in selling the full suite of Cloud and AI infrastructure solutions. You will help them position data center virtualization and systems architecture solutions effectively against competing offerings. You will be passionate about pre-sales engineering activities, demonstrating solutions and architectures in Cloud and AI infrastructure.
Your Impact
You will build awareness, fostering education and driving energy for AI with both internal and external team members, partners, etc. You will also act as a link between technical teams, account teams, executives, partners/customers. In addition, you will show case Data Center Networking, Compute and AI solutions/products, its potential and promote its tactical and technical responsibilities. You will play an important role in the design, development and promotion of these Solutions and address challenges. You will need to travel as needed to meet with clients and attend industry events.
Minimum Qualifications:
Preferred Qualifications:
• Bachelor's Degree in Computer Science, Computer Engineering, Electrical Engineering, or related field. Advanced degree is a plus.
• 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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