23 hours ago
Singapore (city not specified)Senior
Responsibilities
- Lead and manage complex consulting engagements, project delivery, and customer satisfaction.
- Design and implement Red Hat OpenShift, AI platform, and enterprise Agentic AI architectures.
- Deploy and manage AI workloads on OpenShift and Kubernetes platforms across hybrid- and multi-cloud environments.
- Design Agentic AI solutions involving multi-agent frameworks, workflow orchestration, planning, memory, tool integration, and governance.
- Lead customer discovery, analysis, design, and technical workshops that influence architecture decisions.
- Manage project status and communicate with internal and external stakeholders.
- Mentor and develop consultants and foster collaborative project teams.
- Define best practices for platform deployment, hardening, observability, monitoring, alerting, capacity, scalability, resiliency, and security operations.
- Support technical pre-sales efforts and advise customers on enterprise AI adoption.
- Contribute to internal methodologies, reference architectures, and shared consulting assets.
Requirements
- 10+ years of experience in consulting, solution architecture, or technical advisory roles.
- Advanced hands-on experience with Red Hat OpenShift and multiple Kubernetes clusters across multi-cloud environments.
- Strong MLOps experience covering model training, fine-tuning, deployment, monitoring, governance, and lifecycle management.
- Experience with AI/ML frameworks such as 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 Agentic AI solutions, multi-agent frameworks, workflow orchestration, planning, memory, tool integration, and AI agent governance.
- Hands-on experience with LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar Agentic AI frameworks.
- Experience implementing the Model Context Protocol to integrate LLMs with enterprise applications, APIs, data sources, and business systems.
- Experience building secure, scalable, governed AI solutions with authentication, authorization, observability, guardrails, and responsible AI practices.
- Experience with model serving, experiment tracking, model registries, feature stores, and inference optimization.
- Strong knowledge of GPU infrastructure, AI accelerators, and workload scheduling for high-performance AI environments.
- Experience integrating AI platforms with cloud-native services across hybrid- and multi-cloud environments.
- Knowledge of data pipelines, feature engineering, data governance, and data quality for AI workloads.
- Proven leadership in AI, data, and platform modernization initiatives and enterprise-scale transformations.
- Strong customer-facing, workshop facilitation, presentation, communication, and advisory 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 technologies is highly desirable.
Benefits
- Red Hat associates work flexibly across in-office, office-flex, and fully remote environments depending on role requirements.
- Red Hat promotes an open, inclusive, collaborative, and equal-opportunity workplace.
- Reasonable accommodations are available to applicants with disabilities.
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.