Red Hat

Senior AI Platform Specialist Solution Architect

Red Hat • $172K — $275K *
US-Anywhere
+ 3 other locationsRemote
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 4+ years of hands-on experience with Kubernetes and containerized environments.
  • Proven experience in configuring and optimizing AI/ML workloads on Kubernetes.
  • Practical experience in building AI applications using Python and OSS frameworks like TensorFlow or PyTorch.
  • Experience in designing data and ML pipelines for AI systems.
  • Familiarity with CI/CD solutions in MLOps and Infrastructure as Code (IaC) tools like Ansible.
  • Strong public speaking skills and ability to deliver technical presentations.

Responsibilities

  • Identify and address challenges to drive Red Hat AI adoption in customer accounts.
  • Plan and execute AI systems, including data and ML pipeline architecture.
  • Facilitate technical deep dives and proofs of concept for customers.
  • Act as an advocate for AI stakeholders within customer organizations.
  • Provide market feedback to the AI business unit and engineering teams.
  • Engage in community outreach and customer advocacy through speaking and writing.

Benefits

  • Comprehensive medical, dental, and vision coverage.
  • Flexible Spending Account for healthcare and dependent care.
  • Health Savings Account for high deductible medical plans.
  • 401(k) retirement plan with employer match.
  • Paid time off and holidays.
  • Paid parental leave for all new parents.
  • Employee stock purchase plan and tuition reimbursement.
Full Job Description
About the role:

The Red Hat North America Technology Sales team is looking for an AI Platform Specialist Solution Architect (SSA) to join our team. This position assumes a crucial role in providing expert deep technical sales support for the seamless execution of Go-To-Market (GTM) strategies related to Red Hat AI within North American 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.

You will need to be able to confidently articulate our value proposition to leadership, data scientists, developers, and IT teams within the account. This will entail technical architecture walk-throughs, business-value conversations, customer-facing technical workshops, and implementation of best practices in AI systems implementation and design.

You will work closely with the AI business unit and engineering, helping to test, document, and demonstrate cutting-edge features. You will also work in close collaboration with Red Hat customer sales, Customer Success, Consulting Services, and partner teams to ensure a highly positive customer experience.

What you will do:
  • 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


What you will bring:
  • Kubernetes & Container Platform Expertise: 4+ years of hands-on experience architecting, deploying, and managing production-grade containerized environments, with deep technical expertise in Kubernetes. Solid understanding of cluster operations, software-defined networking, persistent storage, and cluster security.
  • Infrastructure for AI/ML Workloads: Proven experience configuring, optimizing, and scheduling containerized workloads on Kubernetes, specifically involving specialized hardware resource management (such as GPU scheduling, NVIDIA Operators, or Multi-Instance GPU configuration).
  • Practical experience in one of the following areas:
    • Machine Learning Use Case Development, including:
      • building AI applications (e.g., deep learning, LLM/RAG, NLP, computer vision, or pattern recognition).
      • Practical experience with a statistical programming language (e.g., Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch).
    • 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


Nice to have:
  • 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


The salary range for this position is $172,020.00 - $275,360.00 (inclusive of base pay + target incentive compensation). Actual offer will be based on your qualifications.

Pay Transparency

Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat's compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience.

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
• Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more!

Note: These benefits are only applicable to full time, permanent associates at Red Hat located in the United States.

About Red Hat

Red Hat, Inc. is a leading provider of open source software solutions, including Linux, Kubernetes, and Ansible. The company was founded in 1993 and is headquartered in Raleigh, North Carolina. Red Hat operates in over 100 countries and has more than 13,000 employees worldwide. The company is committed to open source innovation and has a strong community of developers and partners. Red Hat was acquired by IBM in 2019 and is now part of IBM's Hybrid Cloud division.
Learn more about Red Hat
Size
13,000 employees
Industry
Founded
1993

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