Cisco Solutions Engineer 

United States, Georgia, Atlanta 

116746026

The application window is expected to close on: 9/9/25

NOTE: Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.

Applicants are expected to live within the regions noted in the requisition - those who

live outside of the eastern US will not be considered for this geo specific role.

The Cloud + AI Infrastructure team delivers a scalable strategy with localized

Americas go-to-market engine for compute and data center networking, capturing

Working alongside our colleagues, Cloud & AI Infrastructure develops sales

strategies, activates sellers and technical communities, and accelerates the sales

Your Impact

sales team. In this role, you will drive the adoption of our AI infrastructure solutions

across various industries. You will identify potential clients, understand their specific

position requires a deep understanding of AI infrastructure technologies and

experience in conveying technical concepts to a diverse audience.

You will build awareness, foster education, and drive enthusiasm for AI among

internal team members, external partners, and other stakeholders. You will serve as a

partners/customers. Additionally, you will showcase Cisco AI infrastructure solutions,

highlighting their potential and promoting their tactical and technical benefits. You will

play a vital role in the design, development, and promotion of AI solutions,

addressing any challenges that arise. Travel will be required as needed to meet with

clients and attend industry events.

Minimum Qualifications

4+ years of technical pre-sales experience selling compute, storage, and network solutions or similar cloud-based AI infrastructure.

Understanding and experience with AI/ML (Transformers, Deep Neural Networks, Reinforcement learning, ETL, Data Engineering, Data Processing PyTorch, Model Operations, AI Frameworks e.g. Langchain or similar)

Understanding of hardware accelerators like GPUs and DPUs, including how they are utilized and sized to scale AI infrastructure.

Preferred Qualifications

Bachelor’s degree in computer science, Computer Engineering, Electrical Engineering or a related field. An advanced degree is a plus.

Excellent presentation and communication skills, with the ability to deliver engaging workshops on AI topics to both technical and non-technical audiences.

Experience with AI solutions from vendors such as Nvidia, AMD, Intel, Microsoft, Google, Meta, Dell, HPE, and other AI vendors.

In-depth understanding of language models, including but not limited to GPT-3, LLaMA, BERT, or similar architectures.

Experience in deploying large language models (LLMs) from Hugging Face in training, fine-tuning and distributed inferencing environments.

Familiarity with popular AI frameworks such as PyTorch and TensorFlow

Experience with popular databases like Oracle, MySQL, and MongoDB. AI vector databases like Chroma and AI data platforms like VAST

Experience with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) for scalable and efficient model deployment.