Consultant, OpenShift AI - Top Secret Clearance Required
About the Job
What you will do
Red Hat customers aim to personalize AI across three core areas: their models, their data, and their operational AI. Your responsibilities align directly with these key pillars:
- Guide customers in implementing scalable, production-ready AI solutions using Red Hat OpenShift and Red Hat AI.
- Deploy, optimize, and serve AI models (vLLM, KServe, model registries, pipelines) and baseline inference costs using benchmarking tools and recipe-based optimization.
- Implement retrieval and context patterns (RAG, context ingestion, permission-aware context) and evaluate model performance using tools like Eval Hub to ensure release quality.
- Configure and maintain Models-as-a-Service and GPU-as-a-Service capabilities on OpenShift AI, including multi-tenancy, AI gateways, metering, and self-service accelerator access across NVIDIA, AMD, and other hardware.
- Build and integrate agentic systems and automation workflows using Ansible Automation Platform and modern agent frameworks (MCP, A2A, OpenAI-compatible APIs, LangGraph, etc.) with security, RBAC, and audit ability built in.
- Continuously learn, grow, and adapt to new skills, AI frameworks, and technologies while sharing knowledge, runbooks, and recipes back to internal communities of practice.
- Travel weekly, Monday-Thursday, to client locations.
What you will bring
- Required Experience: • Experience with delivering an implementation based on an architectural design.
- Demonstrated ability to collaborate on project timelines and maintaining project and technical documentation.
- Experience working collaboratively across diverse teams and stakeholders.
- Technical Skills: • Current OpenShift expertise: cluster architecture, GitOps, multi-cluster management, security and observability, GPU-enabled nodes.
- Experience with Red Hat AI or its upstreams: OpenShift AI, vLLM, model serving with KServe, model registries and pipelines, and at least one of llm-d, LLM Compressor or Eval Hub.
- Working knowledge of how enterprises run generative AI today: inference economics, model selection and optimization, RAG and evaluation, agent frameworks and harnesses, MCP, and the governance and cost pressures that shape production decisions.
- Application development fluency on Kubernetes: containers, APIs, CI/CD and the trusted software supply chain (SBOM, signing, policy gates), in at least one of Python, Go or Java.
- Hands-on experience with Ansible Automation Platform for enterprise automation, including event-driven workflows, or the capability to rapidly transition skills from comparable tools.
- Experience delivering hands-on technical implementations based on architectural designs in enterprise environments.
- Ability to meet stakeholder needs and carry-out expectations regarding project timelines, technical deliverables, and scope of work.
- Experience working collaboratively across diverse technical teams, platform engineers, and customer stakeholders.
- Knowledge and desire to mentor team members and customer engineers to foster self-sufficiency.
After joining Red Hat,
here's how your skill set will evolve and what you'll learn during your first year in the role. An intensive customized enablement program on Red Hat AI technologies and Services solutions will layer on AI specifics.
In two months, be prepared to join a project team by acquiring the following:
- Understanding of how to build production-ready technical solutions integrated with existing enterprise systems.
- Learn technologies and consulting skills to enhance your abilities through enablements designed and taught by Red Hat experts and certification.
- Through everyday networking and community events, gain exposure and collaboration within Red Hat Services & the more prominent organization.
Within six months, be ready to support customer success on a project by attaining the following:
- Successful, collaborative delivery of customer projects as a technical lead through expertise in Red Hat's technologies.
- Knowledge of how a customer use case can be developed into a project plan and how those requirements align with Red Hat's technologies.
- Continue expanding your knowledge and network, both internal and external, through enablement, communities, customers, and meetups.
Within 12 months, demonstrate technical leadership by accomplishing the following:
- Successfully implementing complex, large-scale solutions in customer environments.
- Active engagement and knowledge sharing with our internal and external communities of practice on lessons learned, best practices, and how-tos.
The salary range for this position is $96,440.00 - $154,190.00. Actual offer will be based on your qualifications.
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