Solutions Engineer - Artificial Intelligence (AI) Practitioner

About the role

Cisco is looking for a Solutions Engineer - Artificial Intelligence (AI) Practitioner to join its sales team. As an AI Solutions Engineer, you will consult with potential clients, understand their needs and help them adopt Cisco's AI solutions across industries. You will work within the Cloud and AI Infrastructure organization, helping customers transform their businesses through AI, data center, networking and cloud technologies.

Key responsibilities

• Work with customers, partners, sales teams, product specialists and product engineering teams to turn customer problems into deployable solutions.
• Design and document enterprise technology solutions using established architecture and deployment methodologies.
• Develop and demonstrate practical AI solutions that address real-world business problems.
• Lead customer workshops, architecture discussions, demonstrations and technical evaluations.
• Communicate clearly and present confidently, using hands-on demonstrations to explain complex ideas to technical and non-technical audiences.

Required profile

• 10+ years of experience in technology consulting or pre-sales, preferably in software, data, analytics, infrastructure, AI or related fields.
• Strong understanding of machine learning, deep learning, generative AI and modern AI application architectures.
• Ability to discuss model architectures with data scientists, infrastructure requirements with platform teams and business outcomes with executives.
• Preferred: Bachelor's degree in Computer Science, Computer Engineering, Data Science or a related field; advanced degree a plus.

Required skills

• Programming and scripting, particularly Python.
• Experience with AI infrastructure such as GPU systems, networking, storage, cloud services or container platforms.
• Preferred: GPU accelerators, InfiniBand or RoCE, scale-out storage, model-serving frameworks (vLLM, NVIDIA NIM, Triton Inference Server, TensorRT-LLM).
• Preferred: PyTorch, TensorFlow, Jupyter, NVIDIA AI Enterprise, Kubernetes, OpenShift, containerization, MLOps.