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Job Summary
Your primary focus will be to remove organizational, technical, and competitive blockers of adoption within key accounts to become the preferred AI platform for workloads and applications across the business and help our customers leverage their proprietary data to gain a sustainable advantage over their competitors by helping them train, build, and manage applications that rely on these models.
Primary Responsibilities:
Work with the customer Account Executive, Sales Specialist, and Solution Architect to identify challenges and blockers to drive Red Hat AI within new and existing customer accounts.
Plan, design, and execute AI systems with customers having the ability to architect and build data pipelines, ML pipelines, and ML training and serving approaches leveraging additional support and resources from Red Hat as required.
Facilitate pre, and post-sales activities when needed, including technical deep dives, proofs of concept, “bake-offs,” internal sprints and hackathons, and development of partner vertical-specific AI solutions to drive adoption of Red Hat AI.
Identify and partner with AI customer stakeholders, acting as an advocate within both their line-of-business and internal customer teams.
Work closely with the AI business unit and engineering teams, providing a market feedback loop on the product and solutions.
Execute community outreach and customer advocacy activities including conference speaking, blog posts, etc.
Required Qualifications
SME with 4+ years of hands-on experience in one of the following areas:
Machine Learning Use Case Development, including:
Practical experience with a statistical programming language (e.g., Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch).
Building AI applications (e.g., deep learning, LLM/RAG, NLP, computer vision, or pattern recognition).
Machine Learning Operations design, including:
Previous successful experience in AI systems design, with the ability to architect and explain data pipelines, ML pipelines, and ML training and serving approaches.
Experience with CI/CD solutions in the context of MLOps and LLMOps including automation with Infrastructure as Code (IaC) solutions (e.g. Ansible).
Experience delivering technical presentations and leading business value sessions.
Executive presence with public speaking skills.
Preferred Qualifications
Computer Science or similar degree.
Previous experience as a sales engineer, technical sales, or similar role preferably at an enterprise software company, a SaaS company, or Systems Integrator.
Previous experience as an implementation consultant for AI solutions.
Previous experience in Machine Learning Use Case Development and Operations experience.
Industry vertical experience with Data Science projects. i.e. - expertise in FSI, medical, defense, and intelligence verticals.
Community brand in volunteer tech communities like AI Users Group or open-source projects.
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