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Cisco AI Solutions Engineer 
United States, Georgia, Atlanta 
555590057

17.12.2024
Application Deadline expected to close on 12/20/24:
What You’ll Do

We are seeking a Solutions Engineer - Artificial Intelligence (AI) to join our dynamic 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 needs, and provide tailored solutions that enhance their business operations. This position requires a deep understanding of AI infrastructure technologies and experience in conveying technical concepts to a diverse audience.

Who You Are

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 crucial link between technical teams, account teams, executives, and 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:
  • 6+ years of technical pre-sales experience selling compute, storage, and network solutions.
  • 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)
  • Experience with Python or Rust (must)
  • Experience with 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.
  • Experience with AI solutions from vendors such as Nvidia, AMD, Intel, Microsoft, Google, Meta, Dell, HPE, and others
  • Experience with Large scale Cloud, on premises and in memory Databases, Git, AWS, Azure, GCP, IBM Cloud, or other platforms and commonly used programming languages.
  • Familiarity with deploying models in production environments, including cloud, edge, and on-premises solutions.
  • Experience with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes), serverless and other deployment technologies for scalable and efficient model deployment.
  • Excellent presentation and communication skills, with the ability to deliver engaging workshops on AI topics to both technical and non-technical audiences.
  • Proven soft skills such as collaboration, problem-solving, customer engagement and advocacy.

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 at our core (we get 10 days off each year to do just that).