Senior Consultant, OpenShift AI, Top Secret Clearance Required

The Red Hat Services team is looking for a Senior Consultant to implement practical AI solutions that directly solve client challenges using Red Hat OpenShift and Red Hat AI. In this role, you are hands-on throughout technical deployments on engagements that produce tangible outcomes—such as cost-optimized inference, model services with integrated chargeback, or operationalized AI agents. You will work closely with customer teams to turn defined goals and delivery dates into fully landed, functional implementations. To help customer platform teams sustain success long after delivery, you will establish reusable assets on every engagement, including reference architectures, runbooks, and harnesses.

You will act as a key advocate for Red Hat AI solutions, combining technical experience with strong interpersonal skills to solve client problems and scale enterprise AI deployments. Ideal candidates combine a strong background in open-source AI frameworks with a solid grasp of business processes.

We seek people excited about working with us and growing their careers at Red Hat. We want to be transparent about what would make you most successful in the role, and if you are excited by reading the job description and feel you are suitable for the part, we encourage you to apply.

This position requires candidates to work on-site with clients throughout specified locations, so a willingness to travel to customer locations for about 30-40 weeks per year throughout North America is required. Successful applicants must reside in a state where Red Hat is registered to do business and hold an Active Top Secret Clearance.

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…