Engineering Manager | GenAI| LLM | MLops

Randstad Singapore; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Randstad Singapore is seeking a senior engineering leader to scale and mentor a high-performing AI engineering team. You will own the architecture and end-to-end deployment of enterprise-scale generative AI and LLM applications in healthcare, working with cross-functional partners to translate models into production products.

The role requires 8+ years in software/ML/AI, 3+ years managing technical teams, and deep hands-on experience with Python, PyTorch, Hugging Face, and cloud platforms like

Qualifications

• 8+ years in software, ML, or AI engineering.
• 3+ years managing technical engineering teams.
• Proven track record delivering production-grade AI and LLM applications.

Responsibilities

• Team Leadership: Scale, mentor, and guide a high-performing engineering team building production-ready AI solutions.
• System Architecture: Drive the design and end-to-end deployment of enterprise-scale generative AI and LLM applications.
• Agentic Frameworks: Direct the development of multi-agent workflows, tool integrations, and orchestration systems.
• MLOps & Quality: Establish robust AI engineering practices covering model evaluation, CI/CD, and deployment optimization.
• Cross-Functional Strategy: Partner with research and product teams to translate AI models into commercial products.
• Emerging Tech: Evaluate and adopt new AI frameworks to boost product quality and team productivity.

Skills

Python

PyTorch

Hugging Face

Prompt engineering

RAG architectures

Agentic orchestration

Docker

Kubernetes

GCP

Azure

LLMs

Job description

Leadership role! Healthcare with AI, People Management + technical expertise

about company

I am currently working with a leading global technology group expanding its specialized healthcare AI division. They build advanced digital cloud platforms and intelligent systems to streamline and optimize complex clinical workflows.

about job

• Team Leadership: Scale, mentor, and guide a high-performing engineering team building production-ready AI solutions.
• System Architecture: Drive the design and end-to-end deployment of enterprise-scale generative AI and LLM applications.
• Agentic Frameworks: Direct the development of sophisticated multi-agent workflows, tool integrations, and orchestration systems.
• MLOps & Quality: Establish robust AI engineering practices covering model evaluation, continuous testing, CI/CD, and deployment optimization.
• Cross-Functional Strategy: Partner with research and product teams to translate cutting-edge AI models into commercial products.
• Emerging Tech: Evaluate and adopt new AI frameworks to continually boost product quality and team productivity.

Skills and Requirements

• Experience: Minimum 8+ years in software, ML, or AI engineering, including 3+ years managing technical engineering teams.
• Track Record: Proven success delivering production-grade AI and LLM applications.
• Core Tech Stack: Hands-on mastery of Python, PyTorch, and the Hugging Face ecosystem.
• Generative AI & Agents: Deep expertise in fine-tuning, prompt engineering/tool calling, RAG architectures, and agentic AI orchestration.
• Cloud & Infrastructure: Proficiency with cloud-native engineering (Docker, Kubernetes, GCP, or Azure) and inference optimization.
• Strong Plus: 5+ years dedicated experience with LLMs, Python, and Google Cloud Platform (GCP).