Lead AI Engineer | Healthcare Solutions | GenAI and LLM

Randstad · Singapore

Sector
AI
Function
Product & Engineering
Level
Lead
Employment type
Full Time
Posted
2026-08-16
Source
mycareersfuture

Engineering Leader: Healthcare AI (People Management + Technical Architecture)about companyJoin a global technology powerhouse scaling its specialized Healthcare AI division. We build mission-critical digital cloud platforms and intelligent systems that transform complex clinical workflows-directly improving how care is delivered worldwide.about jobInspire, mentor, and grow a elite engineering team building production-ready, high-impact AI solutions.Drive end-to-end design and deployment for enterprise-grade generative AI and advanced LLM applications.Direct the creation of sophisticated multi-agent workflows, tool integrations, and next-gen orchestration platforms.Establish world-class AI engineering standards across model evaluation, continuous testing, CI/CD, and inference optimization.Partner closely with Research and Product leaders to turn cutting-edge AI breakthroughs into commercial products.Continuously evaluate and adopt emerging AI frameworks to push the boundaries of product quality and team output.Skills and RequirementsMinimally 8 years in Software/AI engineering or ML, with at least 3 years successfully leading technical engineering teams.Hands-on experience delivering production-grade AI/LLM applications at scale.Deep mastery of Python, PyTorch, and the Hugging Face ecosystem.Expertise in fine-tuning, prompt engineering/tool calling, RAG architectures, and multi-agent systems.If possible, strong background in cloud-native engineering (Docker, Kubernetes, GCP, or Azure) and inference optimization.Exposure to 5 years focused experience with LLMs, Python, and Google Cloud Platform (GCP).To apply online please use the 'apply' function, alternatively you may contact Evangeline. (EA: 94C3609/ R24124002)

Apply on mycareersfuture →
AI TensorFlow Multi-Agent Systems Ai Microsoft Azure Generative AI Application Development and Deployment Kubernetes Artificial Intelligence