Senior Consultant - AI/ML/OpenShift

About the role

The Red Hat Consulting team is looking for a Senior Consultant to join its Singapore team. You will promote the adoption of Red Hat solutions at key enterprise accounts, government agencies and service provider partners, defining requirements and delivering solutions from the Red Hat portfolio while coaching and mentoring others.

Key responsibilities

• Lead and manage complex consulting engagements, oversee project delivery and keep customers satisfied.
• Design and implement Red Hat OpenShift and AI platform architectures, including deploying and managing AI workloads on OpenShift containers.
• Design and implement enterprise Agentic AI solutions using multi-agent frameworks, workflow orchestration, planning, memory, tool integration and AI agent governance.
• Deliver discovery, analysis and design workshops that shape customer architecture decisions.
• Mentor consultants, support technical pre-sales and workshops, and act as a trusted advisor to technical Red Hat and customer resources.
• Contribute to Red Hat's internal methodologies, reference architectures and shared consulting assets.

Required profile

• 10+ years of experience in consulting, solution architecture or technical advisory roles.
• Proven leadership in AI, data and platform modernization initiatives, able to define technical strategy and deliver enterprise-scale transformations.
• Strong customer-facing skills: leading technical workshops, presenting AI strategies and advising customers on enterprise AI adoption.
• Excellent communication and facilitation skills with technical and business stakeholders.
• Experience contributing to open-source AI/ML communities is highly desirable.

Required skills

• Hands-on experience with Red Hat OpenShift and Kubernetes clusters across multi-cloud environments.
• Expertise in MLOps, including model training, fine-tuning, deployment, monitoring, governance and lifecycle management.
• AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face; Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel.
• Generative AI with LLMs, RAG, vector databases, embedding models and knowledge graphs; Model Context Protocol (MCP).
• Enterprise AI platforms such as Red Hat AI, Red Hat OpenShift AI, NVIDIA AI Enterprise, Kubeflow, MLflow, KServe are highly desirable.
• Knowledge of GPU infrastructure, AI accelerators, data pipelines, feature engineering and data governance.