WHO YOU’LL WORK WITH

You’ll be an integral Cloud + AI Infrastructure team member, which acts as the strategic go-to-market engine for data center transformation and growth across the Americas. You will collaborate with internal teams, including sales, engineering, product development, partners, and customers. Your work will enable the broader team to capitalize on emerging market trends, activate new opportunities to position Cisco datacenter solutions and drive client transformation. You will engage with cross-functional teams to share insights, align on best practices, and amplify your impact in the AI infrastructure space.

MINIMUM QUALIFICATIONS:

• 6+ years of Technical Consulting Experience: Proven track record of advising and guiding clients through complex technological transitions, focusing on the successful adoption and integration of innovative infrastructure solutions.
• 2+ years of Technical Pre-Sales Experience: Proven experience in technical pre-sales, specifically in designing and selling datacenter solutions while effectively communicating the value to clients.
• AI/ML Experience: In-depth experience AI/ML technologies, including working with advanced models such as Transformers, Deep Neural Networks, and Reinforcement Learning. Strong proficiency in working with AI frameworks such as TensorFlow, PyTorch, and LLM development tools. Experience building AI pipelines that streamline the model development and deployment process, ensuring smooth integration with application and infrastructure resources. Experience with hardware accelerators such as GPUs and DPUs, with knowledge of their utilization and sizing to scale AI infrastructure effectively for various use cases.
• Programming Skills: Must possess solid programming experience in Python or Rust, demonstrating the ability to develop, optimize, and deploy AI and data-centric applications.

PREFERRED QUALIFICATIONS:

• Education: Bachelor’s degree in computer science, Computer Engineering, Electrical Engineering, or a related field. An advanced degree is a plus.
• Consultative Approach and Strategic Insight: Exceptional consultative skills to guide education, government, and healthcare institutions through strategic discussions on the value of adopting AI solutions. Capable of uncovering opportunities for AI implementation that align with the institution’s mission and goals.
• Technical Pre-Sales Expertise: Proven experience in a pre-sales role engaging with public sector agencies and institutions to understand their unique challenges and develop comprehensive AI infrastructure solutions. Skilled in communicating complex technical concepts effectively to various stakeholders, from technical teams to senior leadership.
• Experience with AI Software Development: Practical experience developing, deploying, and optimizing AI software. Familiarity with distributed computing frameworks (e.g., Apache Spark, Dask), parallel computing paradigms, and performance optimization for machine learning models. Skilled in Python, C++, and Rust, as well as libraries and tools specific to AI model development.
• AI Hardware Proficiency: Expertise in hardware accelerators like NVIDIA GPUs (e.g., A100, H100) and DPUs, understanding their role in boosting AI performance and scaling large models for various applications.
• Public Sector Use Case Knowledge: Understanding of AI use cases across the public sector, including:

• Citizen Services: AI-driven chatbots, automated response systems, and data analysis to enhance public service delivery and improve government-citizen interactions.
  • Education: AI tools that personalize learning experiences, provide predictive insights for student performance, and optimize administrative operations for educational institutions.

  • Healthcare: Advanced AI applications that power medical research, streamline patient data management, enable predictive analytics for disease prevention, and support health solutions for broader patient access.

• Value of Full-Stack AI Solutions: Demonstrated ability to articulate the value of full-stack AI solutions that span the entire lifecycle—from data collection and preprocessing to model training, deployment, and optimization. Emphasize how integrating software, hardware, and infrastructure ensures seamless execution and performance, minimizes compatibility issues, and reduces the time-to-value for AI projects.

• Understanding Datacenter Infrastructure for AI: Understanding of datacenter infrastructure requirements to support AI workloads. This includes familiarity with research computing clusters, scalable storage solutions like NVMe, and ethernet network capabilities needed for data-intensive AI operations and how to optimize resource allocation for AI workloads. understanding of high-performance computing environments in universities and medical research institutions is a plus.
• Cloud and Hybrid Expertise: Ability to design and implement cloud, on-premises, and hybrid solutions that cater to specific needs. Strong ability to highlight the benefits of on-premises solutions, such as enhanced data security, full control over data and resources, lower latency for real-time applications, and cost predictability for high-volume AI workloads.
• Engaging Communication and Presentation Skills: Capable of developing and delivering impactful presentations and workshops that demonstrate the strategic and technical benefits of full-stack AI solutions to diverse audiences.
• Collaborative Team Player: Strong record of working with cross-functional teams, including sales, engineering, and product development, to deliver comprehensive solutions that align with client goals.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform crucial job functions, and receive other benefits and privileges of employment. Please contact us to request accommodation.

As a Solutions Engineer – Artificial Intelligence (AI), you will serve as a trusted technical leader and advisor, specializing in positioning comprehensive AI solutions in public sector SLED. You will collaborate with data and research scientists, application developers, and IT professionals at educational institutions (higher education and K-12), healthcare organizations, and state and local government agencies. In this pre-sales role, you will work closely with stakeholders to identify impactful AI use cases, assess infrastructure needs, and design full-stack solutions that drive client success. You will navigate the complexities of both on-premises and cloud-based solutions, effectively articulating the strategic benefits and value of each approach. This position requires a strong combination of technical expertise, consultative abilities, and the capacity to communicate complex technical concepts clearly to audiences ranging from engineers to executives.