We are seeking a Solutions Engineer to join our dynamic sales team. As an SE, you will drive the adoption of our AI solutions across various industries. You will identify potential clients, understand their specific needs, and provide tailored AI 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 presales engineering activities, demonstrating solutions and architectures in Cloud and AI infrastructure.
Who You’ll Work With
Who You Are
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 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 AI Solutions and address challenges. You will need to travel as needed to meet with clients and attend industry events.
Minimum Qualifications
- 5+ years knowledge of any combination of Datacenter, Storage, Compute, Apps, Big Data, Converged Infrastructure, AI infrastructure or Data Center Networking experience preferred. 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
- 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.
We tackle whatever challenges come our way. We have each other’s backs, we recognize our accomplishments, and we grow together. We celebrate and support one another – from big and small things in life to big career moments. And giving back is in our DNA (we get 10 days off each year to do just that).