Artificial Intelligence Architect

Key Responsibilities

Owns the full lifecycle of AI solutioning—from discovery to deployment—driving business impact through scalable, customer-centric AI architectures.

* Engage customers to identify and shape AI use cases aligned to business goals

* Translate requirements into scalable end-to-end AI architectures

* Lead pre-sales activities (solutioning, demos, POCs, RFPs)

* Act as trusted technical advisor to CXOs and stakeholders

* Design and position AI-driven solutions (GenAI, analytics, automation)

* Drive rapid prototyping and innovation (POC → MVP → scale)

* Integrate AI solutions with enterprise systems and data platforms

* Ensure security, governance, and Responsible AI compliance

* Collaborate with partners, ISVs, and internal teams for delivery

* Bridge pre-sales to implementation ensuring successful deployment

* Define and track business value, ROI, and outcomes

* Evangelize AI through executive presentations, workshops, and thought leadership

* Design end-to-end AI architectures leveraging NVIDIA AI Enterprise and GPU-accelerated infrastructure

* Architect real-time video analytics pipelines using NVIDIA Metropolis and DeepStream

* Implement and customize NVIDIA Blueprints for production-ready deployments

* Integrate NVIDIA Video Search and Summarization (VSS) into operational command center workflows

* Design scalable edge-to-cloud AI frameworks optimized for live venue environments

* Architect digital twin and simulation environments leveraging NVIDIA Omniverse

* Define multimodal AI architectures combining computer vision, speech AI, and generative AI workflows

* Support real-time avatar and digital human applications powered by NVIDIA ACE and related technologies

* Establish performance, scalability, and governance standards for AI deployments

* Collaborate cross-functionally with engineering, infrastructure, and product teams

Required Qualifications

· Bachelor's Degree in Computer Science or related field

· 8+ years of experience in AI/ML architecture, distributed systems, or enterprise AI platforms

· Strong hands-on experience with:

o NVIDIA AI Enterprise

o NVIDIA Metropolis and DeepStream

o NVIDIA Blueprints

o CUDA and GPU optimization

· Experience designing real-time computer vision and video analytics systems

· Experience building edge-to-cloud AI architectures

· Expertise in containerized AI workloads (Docker, Kubernetes)

· Strong understanding of high-performance computing environments

Preferred Qualifications

· Experience with NVIDIA Video Search and Summarization (VSS)

· Experience with NVIDIA Omniverse and digital twin frameworks

· Experience with NVIDIA ACE (Avatar Cloud Engine) or real-time digital human workflows

· Familiarity with multimodal AI systems (vision + speech + generative AI)

· Experience in sports venues, smart infrastructure, or real-time operational environments