Key Responsibilities

• Design, engineer, and deploy production-grade AI systems using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic architectures
• Build, maintain, and scale backend services, microservices, APIs, and SDKs that power enterprise AI applications
• Own end-to-end AI solution engineering from architecture design through deployment and operational support
• Implement AI Ops and DevOps best practices, including CI/CD pipelines, automated testing, deployment, monitoring, and system optimisation
• Develop and maintain cloud and hybrid AI infrastructure (AWS or equivalent), ensuring scalability, reliability, and security
• Partner with product, data science, and business teams to translate functional requirements into robust technical implementations
• Ensure AI platforms and services comply with enterprise risk, security, and governance standards
• Conduct technical design reviews, identify system optimisation opportunities, and contribute to engineering best practices

Key Requirements

• Strong hands-on experience in AI engineering and Generative AI systems, including LLM integration, RAG pipelines, prompt orchestration, and agentic frameworks
• Proven experience building and operating production-grade systems rather than research-only or experimentation-focused solutions
• Experience from POCs to production grade is essential
• Solid software engineering background with experience in Python, SQL, and backend API development
• Experience designing and deploying scalable, fault-tolerant systems using microservices architecture
• Practical experience with cloud platforms and hybrid environments
• Experience implementing DevOps / AI Ops practices, including CI/CD, monitoring, logging, and incident management
• Strong collaboration and communication skills, with experience working across global and cross-functional teams
• Experience leading and mentoring teams

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative discipline
• Significant professional experience in AI engineering, platform engineering, or full-stack development
• Prior experience in regulated or enterprise-scale environments is highly advantageous
• Relevant certifications in cloud platforms, AI/ML technologies, or DevOps tooling are a plus
  

For more information you can contact Norean Tan at [email protected]

We regret to inform you that only shortlisted candidates will be notified / contacted.

EA Registration No.: R1434118 - Tan Lee Ying, Norean

iKas International (Asia) Pte Ltd

ROC No.: 200914065E | EA License No.: 16S8086