3 months ago
Singapore, SingaporeSenior
Responsibilities
- Design and build comprehensive, production-ready AI architecture blueprints and reference codebases.
- Package repeatable and extensible architectures as open-source AI Quickstarts.
- Collaborate with semiconductor partners, regional AI programs, software vendors, and other external engineering teams to validate joint architectures and integrations.
- Develop automated testing, evaluation harnesses, and system telemetry to measure latency, throughput, cost, and model quality.
- Incorporate data privacy, secure network perimeters, localized hosting, compliance, and risk-management requirements into solution designs.
- Work across distributed computing, workflow orchestration, generative AI, agentic architectures, model serving, runtime optimization, and regulated deployments.
Requirements
- Bachelor’s or master’s degree in computer science, computer engineering, or a related quantitative field.
- Exceptional hands-on proficiency in Python for machine learning and systems programming.
- Familiarity with Go or C/C++ is highly preferred.
- Strong familiarity with PyTorch and NLP/vision ecosystems including Hugging Face Transformers, datasets, and tokenizers.
- Practical experience deploying containerized applications on Kubernetes or enterprise container orchestration platforms.
- Conceptual and hands-on understanding of model-serving lifecycles, data ingestion, and automated packaging.
- Understanding of distributed computing, cluster schedulers, workflow orchestration, vector databases, LLM orchestration, agentic workflows, model fine-tuning, model-serving runtimes, and hardware optimization.
- Ability to communicate complex technical architectures clearly in English to engineers and technical stakeholders.
- Experience in regulated industries such as financial services, public sector, healthcare, telecommunications, or manufacturing is advantageous.
Benefits
- Technical career progression is based on engineering impact, architectural depth, and autonomous delivery rather than people management.
- Opportunity to contribute to open-source solution blueprints and AI Quickstarts used by the broader community.
- Exposure to emerging hardware platforms, agentic runtimes, and localized enterprise software stacks.
- Red Hat supports flexible work environments ranging from in-office and office-flex to fully remote, depending on role requirements.
- Red Hat provides reasonable accommodations and maintains an open, inclusive, equal-opportunity workplace.
Categories
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.