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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive expertise in Red Hat OpenShift and AI platform architecture, with a strong focus on deploying and managing AI workloads and enterprise solutions. Proven ability to lead complex consulting engagements, mentor teams, and communicate effectively with stakeholders.
Highest-signal resume keywords
Red Hat OpenShift ExpertiseMLOps ManagementAI Platform ArchitectureKubernetes Cluster ManagementEnterprise AI Solutions Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Red Hat OpenShiftMLOpsKubernetesAI Workload DeploymentModel TrainingData EngineeringGenerative AI SolutionsModel Context ProtocolGPU InfrastructureFeature Engineering
Soft Skills
Customer-Facing SkillsCommunication SkillsFacilitation SkillsMentoring
Tools & Technologies
PyTorchTensorFlowScikit-learnHugging FaceLangGraphCrewAIAutoGenSemantic KernelNVIDIA AI EnterpriseKubeflow
Industry Keywords
AI SolutionsConsulting EngagementsPlatform ModernizationOpen-Source AI/MLMulti-Cloud Environments
Tech Stack
Tools & technologiesCloudKubernetesOpenShiftPyTorchScikit-LearnTensorflow
About the role
Key responsibilities & impact- Promote adoption of Red Hat solutions at enterprise accounts, government agencies, and service provider partners
- Define requirements and deliver solutions based on Red Hat’s portfolio of solutions and services
- Lead and manage complex consulting engagements and oversee project delivery
- Design and implement robust solutions and take ownership of system architecture
- Manage and communicate project status with internal and external stakeholders
- Mentor and develop consultants
- Adapt project plans and tasks to customer environment issues
- Design and implement modern platform architectures using Red Hat OpenShift, container orchestration, and automation at scale
- Deliver discovery, analysis, and design workshops influencing customer architecture decisions
- Design and implement Red Hat OpenShift and AI platform architecture
- Deploy and manage AI workloads on Red Hat OpenShift container platforms
- Design and implement enterprise Agentic AI solutions
- Act as a trusted advisor to Red Hat and customer technical resources
- Support technical pre-sales efforts and value-focused workshops
- Define best practices for platform deployment, hardening, observability, monitoring, alerting, capacity management, scalability, resiliency, and security operations
- Contribute to internal methodologies, reference architectures, and shared consulting assets
- Stay current with AI, Kubernetes, platform engineering, and open-source trends
Requirements
What you’ll need- 10+ years of experience in a consulting, solution architecture, or technical advisory role
- Hands-on experience and advanced knowledge of Red Hat OpenShift
- In-depth expertise managing multiple Kubernetes clusters across multi-cloud environments
- Strong expertise in MLOps, including model training, fine-tuning, deployment, monitoring, governance, and lifecycle management
- Experience with PyTorch, TensorFlow, Scikit-learn, Hugging Face, or similar technologies
- Experience designing and operationalizing enterprise Generative AI solutions using LLMs, RAG, vector databases, embedding models, and knowledge graphs
- Experience with enterprise Agentic AI solutions and multi-agent frameworks
- Hands-on experience with LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar
- Experience implementing Model Context Protocol (MCP)
- Experience developing secure, scalable, governed AI solutions with authentication, authorization, observability, guardrails, and responsible AI practices
- Experience implementing enterprise AI platform capabilities, including model serving, experiment tracking, model registries, feature stores, and inference optimization
- Strong knowledge of GPU infrastructure, AI accelerators, and workload scheduling technologies
- Experience integrating AI platforms with cloud-native services across hybrid and multi-cloud environments
- Knowledge of data engineering principles, including data pipelines, feature engineering, data governance, and data quality
- Proven leadership in AI, data, and platform modernization initiatives
- Strong customer-facing skills, including technical workshops, AI strategy presentations, and enterprise AI advisory
- Excellent communication and facilitation skills
- Experience contributing to open-source AI/ML communities or projects is highly desirable
- Experience with Red Hat AI, Red Hat OpenShift AI, NVIDIA AI Enterprise, Kubeflow, MLflow, KServe, or equivalent is highly desirable
Benefits
Comp & perks- Flexible work environments, from in-office to office-flex to fully remote, depending on role requirements
- Equal opportunity workplace and affirmative action employer
- Reasonable accommodations for applicants with disabilities