AI Platform Specialist Solution Architect (SSA) – AI Platform

Job Description

Senior AI Platform Specialist Solution Architect | Red Hat

The Tone:
This is a full-time role at Red Hat, located remotely in the USA. Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. This position is crucial for providing deep technical sales support for the seamless execution of Red Hat AI Go-To-Market strategies within North America, helping customers overcome blockers to AI adoption and leverage their proprietary data to gain a sustainable competitive advantage.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: Remote – USA
• Pay: $172020–$275360 yearly
• Team: Red Hat North America Technology Sales team
• Mission: Remove organizational, technical, and competitive blockers to AI adoption, enabling customers to train, build, and manage AI applications leveraging their proprietary data on Red Hat platforms.
• Tech Stack: Kubernetes, Container Platform, GPU scheduling, NVIDIA Operators, Multi-Instance GPU, Python, TensorFlow, PyTorch, CI/CD, MLOps, LLMOps, Infrastructure as Code (IaC), Ansible

What You’ll Actually Do
• Adoption Driver: Identify and remove organizational, technical, and competitive challenges to drive Red Hat AI adoption within new and existing customer accounts.
• System Architect: Plan, design, and execute AI systems with customers, including architecting and building data pipelines, ML pipelines, and ML training and serving approaches.
• Technical Facilitator: Facilitate pre- and post-sales activities such as technical deep dives, proofs of concept, internal sprints, hackathons, and development of partner vertical-specific AI solutions.
• Customer Advocate: Identify and partner with AI customer stakeholders, acting as an advocate within both their line-of-business and internal customer teams.
• Product Feedback Loop: Work closely with the AI business unit and engineering teams, providing a market feedback loop on product and solutions, and executing community outreach.

The Must-Haves
• Background: Senior-level specialist with deep technical expertise in Kubernetes and container platforms, specifically for AI/ML workloads.
• Experience: 4+ years of hands-on experience architecting, deploying, and managing production-grade containerized environments with Kubernetes. Proven experience configuring, optimizing, and scheduling containerized AI/ML workloads on Kubernetes, including specialized hardware resource management (GPU scheduling, NVIDIA Operators, or Multi-Instance GPU configuration). Practical experience in either Machine Learning Use Case Development (building AI applications like deep learning, LLM/RAG, NLP, computer vision, or pattern recognition with Python, TensorFlow, or PyTorch) OR Machine Learning Operations design (AI systems design, architecting data/ML pipelines, training/serving, and CI/CD with MLOps/LLMOps automation using IaC like Ansible).
• Skills: Kubernetes & Container Platform expertise, specialized hardware resource management for AI/ML, statistical programming (Python), open-source ML frameworks (TensorFlow, PyTorch), AI systems design, MLOps/LLMOps CI/CD, Infrastructure as Code (Ansible), delivering technical presentations, executive presence, and public speaking.
• Bonus: Computer Science or similar degree. Previous experience as a sales engineer, technical sales, or an implementation consultant for AI solutions. Industry vertical experience with Data Science projects (e.g., FSI, medical, defense, intelligence). Community brand in volunteer tech communities or open-source projects.