1 day ago
Responsibilities
- Partner with account executives, sales specialists, solution architects, and customers to identify and remove technical and organizational blockers to Red Hat AI adoption.
- Plan, design, and execute AI systems, including data pipelines, ML pipelines, and ML training and serving approaches.
- Lead technical deep dives, proofs of concept, bake-offs, internal sprints, hackathons, workshops, and business-value sessions.
- Develop partner and industry-specific AI solutions and facilitate pre-sales and post-sales activities.
- Collaborate with AI business-unit and engineering teams to test, document, demonstrate, and provide feedback on product features.
- Act as an advocate for AI customer stakeholders and conduct conference speaking, blog writing, and other community outreach.
Requirements
- At least 4 years of hands-on experience architecting, deploying, and managing production-grade containerized environments with deep Kubernetes expertise.
- Strong understanding of Kubernetes cluster operations, software-defined networking, persistent storage, and cluster security.
- Experience configuring, optimizing, and scheduling Kubernetes workloads using specialized hardware resources such as GPU scheduling, NVIDIA Operators, or Multi-Instance GPU configurations.
- Practical experience developing machine-learning use cases, including 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 open-source frameworks such as TensorFlow or PyTorch.
- Alternatively, experience designing AI systems and MLOps, including data pipelines, ML pipelines, ML training and serving, CI/CD solutions for MLOps and LLMOps, and infrastructure automation with tools such as Ansible.
- Experience delivering technical presentations and leading business-value sessions, with executive presence and public-speaking skills.
- A computer science or similar degree is preferred.
- Previous experience as a sales engineer, technical sales professional, implementation consultant for AI solutions, or enterprise software, SaaS, or systems-integrator professional is preferred.
- Machine-learning operations experience, data-science project experience, industry-vertical expertise, or participation in technology communities and open-source projects is preferred.
Benefits
- Comprehensive medical, dental, and vision coverage.
- Flexible Spending Account and Health Savings Account options.
- 401(k) retirement plan with employer match.
- Paid time off, holidays, paid parental leave, disability leave, paid family medical leave, and paid military leave.
- Employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and other benefits.
- Red Hat supports flexible work environments ranging from in-office and office-flex to fully remote depending on role requirements.
- Benefits listed apply to full-time, permanent U.S. associates.
Tech Stack
Categories
Solutions Engineering
About Red Hat
Red Hat builds enterprise open-source software, including Red Hat Enterprise Linux, OpenShift for Kubernetes, and Ansible automation, sold via subscriptions with support, training, and consulting. It serves large enterprises and public-sector organizations running hybrid and multi-cloud infrastructure and modern application platforms. Founded in 1993 and headquartered in Raleigh, North Carolina, Red Hat operates as an independent subsidiary of IBM.