#EG Platform AI Engineer

NCS Group; Singapore; On-site; SGD 75,000 - 95,000; Full time

Benefits offered by this job

Competitive compensation

Professional development support

Job summary

NCS Group in Singapore is looking for a Platform AI Engineer to join their AI Center of Excellence. In this role, you will develop AI capabilities and integrate services on a scalable platform, while collaborating with engineering teams to ensure operational reliability.

The ideal candidate will have significant experience with Python, AI systems, and working in Kubernetes environments. Join a talented team and enjoy competitive compensation and professional development opportunities.

Qualifications

• 3-5 years of professional software engineering experience.
• 1-2 years of hands-on experience with AI/ML/LLM systems.
• Experience with vLLM or equivalent model serving.

Responsibilities

• Build and enhance AI platform services using Python.
• Integrate AI services with model platforms and data pipelines.
• Collaborate on deployment and reliability in Kubernetes environments.

Skills

Backend or platform services using Python

AI, ML, or LLM-based systems

Containerised and Kubernetes-based environments

Git-based workflows and CI/CD pipelines

LLM integration patterns

Vector databases

Data pipelines (batch and streaming)

Job description

NCS is a leading AI Tech Services company. With a 15,000-strong team across the Asia Pacific, NCS scales its platforms and capabilities to provide clients with greater agility and AI expertise across a range of industries. Embracing a strong ecosystem of global partners, NCS transforms technology services delivery combining AI with digital resilience to drive real business impact. NCS is a subsidiary of the Singtel Group.

Job Description

As a Platform AI Engineer, you will be a hands‑on contributor within the AI Center of Excellence (AI COE), a centralized platform product team that builds and operates enterprise‑grade AI and data platforms. Your focus is on developing shared, production‑ready AI capabilities – such as LLM services, workflows, and platform integrations – that enable internal engineering teams to safely, reliably, and efficiently consume AI at scale.

What will you do?

AI Platform Engineering

• Build and enhance AI platform services using Python and cloud‑native technologies
• Implement AI workflows including RAG pipelines, inference services, and agent‑based logic
• Design AI services with production‑grade considerations such as latency, throughput, resilience, and cost efficiency

Platform Integration

• Integrate AI services with model platforms, AI gateways, vector databases, and inference runtimes
• Integrate with data pipelines (batch and streaming) to support AI workflows
• Work with observability and LLMOps tooling to enable monitoring and operational visibility

Reliability, Deployment & Operations

• Collaborate with platform engineers on deployment, scaling, and reliability in containerised / Kubernetes environments
• Participate in production support, incident resolution, and continuous improvement
• Balance rapid experimentation with enterprise requirements such as security, governance, and compliance

Developer Enablement

• Contribute to shared libraries, SDKs, and internal developer tooling
• Improve platform usability and overall developer experience
• Participate in code reviews, testing, and Git‑based CI/CD workflows

Qualifications

• Strong hands‑on experience building backend or platform services using Python
• 3‑5 years of professional software engineering experience, including work on shared or platform services
• 1‑2 years of hands‑on experience with AI, ML, or LLM‑based systems in production or pre‑production environments
• Experience with LLM integration patterns, including prompt engineering and RAG workflows
• Experience with vector databases (e.g. Milvus) and embedding‑based retrieval
• Understanding of model serving and inference runtimes (e.g. vLLM or equivalent)
• Familiarity with AI gateways and access‑control patterns for LLMs
• Experience integrating with data pipelines (batch and streaming)
• Basic understanding of LLMOps and observability concepts for AI systems
• Experience working in containerised and Kubernetes‑based environments
• Familiarity with Git‑based workflows and CI/CD pipelines
• Strong ownership mindset, collaborative approach, and willingness to learn evolving AI technologies

Why Join NCS

• Lead high‑impact Data & AI advisory programs for major enterprises and public sector clients
• Shape enterprise strategies and governance frameworks that drive real transformation
• Work with a talented, multidisciplinary team in a collaborative environment
• Competitive compensation and strong professional development support