3 months ago
Singapore, SingaporeSenior
Responsibilities
- Design and implement Red Hat OpenShift AI platform architectures.
- Deploy and manage AI workloads on Red Hat OpenShift container platforms.
- Design and implement enterprise agentic AI solutions using multi-agent frameworks, workflow orchestration, planning, memory, tool integration, and governance.
- Lead medium- to large-sized project teams and ensure the quality of customer deliverables.
- Conduct discovery, analysis, design, architecture review, and knowledge-transfer workshops.
- Support technical pre-sales through scoping, technical proposals, solution demonstrations, proofs of concept, and architectural reviews.
- Define best practices for platform deployment, hardening, observability, monitoring, alerting, capacity management, scalability, resiliency, and security operations.
- Act as a trusted technical advisor to Red Hat and customer stakeholders and align solutions with customer requirements and use cases.
- Mentor junior consultants and customer engineers.
- Contribute to internal methodologies, playbooks, reference architectures, and shared consulting assets.
Requirements
- 10+ years of experience in consulting, solution architecture, or technical advisory roles.
- Strong expertise in MLOps, including model training and fine-tuning, deployment, monitoring, governance, and lifecycle management.
- Experience with AI/ML frameworks and libraries such as PyTorch, TensorFlow, Scikit-learn, and Hugging Face.
- Experience designing and operationalizing enterprise generative AI solutions using LLMs, RAG, vector databases, embedding models, and knowledge graphs.
- Experience implementing enterprise agentic AI solutions and hands-on experience with LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar frameworks.
- Experience implementing the Model Context Protocol to integrate LLMs with enterprise applications, APIs, data sources, and business systems.
- Experience developing secure, scalable, governed AI solutions with enterprise 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 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 and enterprise-scale transformations.
- Strong customer-facing, presentation, workshop facilitation, communication, and stakeholder 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 supports flexible work environments ranging from in-office and office-flex to fully remote, depending on role requirements.
- The role supports customers across the ASEAN region from Singapore.
- Red Hat provides reasonable accommodations to applicants with disabilities.
- Red Hat is an equal opportunity workplace and affirmative action employer.
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.