Lead Nvidia AI Consultant

About the role

In this role, you will serve as a technical advisor and thought leader for enterprise AI transformations powered by the Nvidia technology stack — designing, validating, and delivering scalable AI architectures — within SoftServe’s AI and Data Science Center of Excellence. Working closely with clients, Nvidia stakeholders, and internal engineering teams, you’ll drive AI adoption and shape go-to-market solutions that deliver measurable business outcomes.

Responsibilities

• Strategy definition through architecture and implementation
• Translate complex business and operational challenges into AI use-case definitions, solution roadmaps, and reference architectures aligned with client scope
• Support pre-sales activities, including proposals, solution positioning, customer workshops, GenAI proof-of-concept initiatives, and technical discovery sessions
• Design and validate AI architectures leveraging Nvidia technologies, including NeMo, NIM, Triton, Riva, DeepStream, Metropolis, and Omniverse
• Contribute to Nvidia alliance go-to-market strategy by shaping industry offerings, reusable accelerators, demos, and solution blueprints
• Guide organizations on enterprise AI governance, MLOps, model lifecycle management, scalability, observability, and deployment best practices
• Drive thought leadership through whitepapers, technical blogs, conference presentations, demos, and industry events
• Mentor engineering and consulting teams on Nvidia ecosystem technologies

Requirements

• 6+ years of experience in AI consulting, GenAI/Agentic AI development, Machine Learning, and Deep Learning areas
• Hands-on experience with Python and modern AI/ML frameworks, including PyTorch, TensorFlow, Pandas, NumPy, Hugging Face
• Practical experience across the full AI lifecycle, including experimentation, fine-tuning, optimization, deployment, inference, and monitoring
• Experience working with Nvidia AI technologies, including NeMo, NIM, Riva, Metropolis, Omniverse, Triton, or related ecosystem platforms preferred
• Experience designing and deploying AI solutions in at least one cloud environment, like AWS, Azure, GCP
• Understanding of GPU-accelerated AI platforms and inference optimization technologies such as TensorRT, Triton Inference Server, CUDA, DeepStream, ONNX, or similar
• Strong advisory and stakeholder management capabilities with experience presenting to stakeholders, executive, and leadership audiences
• Experience supporting go-to-market initiatives, customer discovery workshops, solution positioning, and technical pre-sales engagements
• Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, Physics, Engineering, or related technical field preferred