Lead AI Engineer
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Lead AI Engineer
Location
Malaysia - Global Development Campus, Johor Bahru
Experience
Senior
Posted
Jul 7, 2026
Apply by
September 30, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Office
Job Description
Join Dyson’s global IT data community and play a key role in designing, building, and scaling enterprise-grade AI systems. You’ll lead technical delivery across squads, working closely with data analysts, product managers, data scientists, and AI/ML Ops engineers to deliver robust AI solutions that drive business impact at scale.
# WHO YOU ARE
You are a highly experienced, hands-on AI engineer who thrives on solving complex problems with scalable, production-grade solutions. You are passionate about building AI systems that move beyond prototypes into robust, observable, and governed platforms that deliver measurable business value.
You demonstrate strong ownership and technical leadership, setting direction for engineering practices while remaining deeply involved in implementation. You are comfortable leading cross-team initiatives, guiding architectural decisions, and raising the overall engineering bar.
You prioritize continuous learning, whether it is exploring new frameworks, experimenting with novel architectures, or deepening your understanding of AI infrastructure. You actively drive adoption of best practices across teams while helping others grow their technical capability.
# WHAT YOU'LL DO
As a Lead AI Engineer you will:
- Lead the design and delivery of robust, scalable AI systems and agentic workflows across squads
- Define architecture patterns for orchestration, multi-step reasoning, tool use, and agent coordination
- Set and enforce standards for context engineering, including prompt design, retrieval augmentation, grounding, and memory systems
- Oversee the development of modular, reusable APIs, services, and integration layers that enable enterprise AI delivery
- Establish evaluation frameworks, quality gates, and continuous improvement loops to ensure system reliability and performance
- Own production monitoring and operational excellence for AI systems, including tracing, observability, debugging, and incident response patterns
- Lead technical decomposition of complex and ambiguous business problems into well-scoped, solvable AI engineering workstreams
- Mentor and guide engineers through design reviews, code reviews, technical planning, and best practice adoption
- Collaborate closely with Data Science, AI/ML Ops, Platform, and Product teams to ensure scalable, secure, and governed delivery
- Define reusable components, frameworks, and engineering standards that accelerate AI solution delivery across teams
- Partner with stakeholders to translate business needs into scalable AI architectures and solutions
- Share learnings, develop standards, and educate the wider business on responsible and effective use of AI
Our global reputation is priceless, and it always hangs on what we do next. Dyson is a unique technology enterprise. We are authentic, different and pioneering. Our biggest category today didn’t even exist a few years ago. Our next biggest category? That could be where you come in.
*Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.*
Key Responsibilities
- Lead the design and delivery of robust, scalable AI systems and agentic workflows across squads
- Define architecture patterns for orchestration, multi-step reasoning, tool use, and agent coordination
- Set and enforce standards for context engineering, including prompt design, retrieval augmentation, grounding, and memory systems
- Oversee the development of modular, reusable APIs, services, and integration layers that enable enterprise AI delivery
- Establish evaluation frameworks, quality gates, and continuous improvement loops to ensure system reliability and performance
- Own production monitoring and operational excellence for AI systems, including tracing, observability, debugging, and incident response patterns
- Lead technical decomposition of complex and ambiguous business problems into well-scoped, solvable AI engineering workstreams
- Mentor and guide engineers through design reviews, code reviews, technical planning, and best practice adoption
- Collaborate closely with Data Science, AI/ML Ops, Platform, and Product teams to ensure scalable, secure, and governed delivery
- Define reusable components, frameworks, and engineering standards that accelerate AI solution delivery across teams
- Partner with stakeholders to translate business needs into scalable AI architectures and solutions
- Share learnings, develop standards, and educate the wider business on responsible and effective use of AI
Skills Required
AI SystemsAgentic WorkflowsOrchestrationMulti-step ReasoningTool UseAgent CoordinationContext EngineeringPrompt DesignRetrieval AugmentationGroundingMemory SystemsAPI DevelopmentService DevelopmentIntegration LayersEvaluation FrameworksProduction MonitoringObservabilityDebuggingIncident ResponseTechnical LeadershipMentoringOwnershipCross-team CollaborationContinuous LearningProblem SolvingCommunication
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