Senior AI Platform Specialist, Solution Architect
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Job Description
AI platform architect helping Red Hat customers adopt Red Hat AI and Kubernetes-based solutions. Designing ML infrastructure, guiding technical sales, and enabling enterprise AI workloads.
Responsibilities:
- Provide expert deep technical sales support for Red Hat AI go-to-market strategies across North American customer accounts
- Remove organizational, technical, and competitive adoption blockers to position Red Hat AI as the preferred AI platform
- Help customers train, build, and manage applications using proprietary data and AI models
- Articulate Red Hat’s value proposition to leadership, data scientists, developers, and IT teams
- Conduct technical architecture walk-throughs, business-value conversations, customer-facing technical workshops, and implement AI systems best practices
- Collaborate with the AI business unit and engineering to test, document, and demonstrate cutting-edge features
- Work with Red Hat sales, Customer Success, Consulting Services, and partner teams to deliver a positive customer experience
- Identify customer challenges and blockers with Account Executives, Sales Specialists, and Solution Architects
- Plan, design, and execute AI systems, including data pipelines, ML pipelines, and ML training and serving approaches
- Facilitate pre- and post-sales technical deep dives, proofs of concept, bake-offs, internal sprints, hackathons, and partner AI solutions
- Partner with AI customer stakeholders and advocate across customer teams
- Provide market feedback to AI business unit and engineering teams
- Execute community outreach and customer advocacy activities, including conference speaking and blog posts
Requirements:
- 4+ years of hands-on experience architecting, deploying, and managing production-grade containerized environments
- Deep technical expertise in Kubernetes
- Solid understanding of cluster operations, software-defined networking, persistent storage, and cluster security
- Experience configuring, optimizing, and scheduling containerized workloads on Kubernetes
- Experience with specialized hardware resource management, such as GPU scheduling, NVIDIA Operators, or Multi-Instance GPU configuration
- Practical experience in machine learning use case development, including building AI applications such as deep learning, LLM/RAG, NLP, computer vision, or pattern recognition
- Practical experience with a statistical programming language such as Python
- Applied machine learning techniques and OSS frameworks such as TensorFlow and PyTorch
- Experience designing AI systems and architecting data pipelines, ML pipelines, and ML training and serving approaches
- Experience with CI/CD solutions in MLOps and LLMOps, including Infrastructure as Code solutions such as Ansible
- Experience delivering technical presentations and leading business value sessions
- Executive presence with public speaking skills
- Computer Science or similar degree is nice to have, not required
- Previous sales engineering, technical sales, implementation consulting, machine learning operations, or industry vertical experience is nice to have
Benefits:
- Comprehensive medical, dental, and vision coverage
- Flexible Spending Account - healthcare and dependent care
- Health Savings Account - high deductible medical plan
- Retirement 401(k) with employer match
- Paid time off and holidays
- Paid parental leave plans for all new parents
- Leave benefits including disability, paid family medical leave, and paid military leave
- Employee stock purchase plan
- Family planning reimbursement
- Tuition reimbursement
- Transportation expense account
- Employee assistance program
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