AI Engineer

SATS Ltd.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

SATS Ltd. is seeking an AI Engineer to build and scale enterprise-grade GenAI platforms, enabling rapid development of LLM-powered applications across the organization. The role focuses on reusable GenAI infrastructure, including RAG pipelines, vector databases, and agent orchestration frameworks.

You will develop scalable model serving layers, manage embedding pipelines, and optimize performance and cost of LLM systems while collaborating with AI/ML teams to accelerate GenAI adoption.

Qualifications

• 3–5 years in AI engineering or backend systems.
• Strong expertise with LLMs, RAG, embeddings.
• Experience with vector databases and model serving.

Responsibilities

• Build and scale GenAI platforms for enterprise use.
• Develop reusable GenAI services and APIs.
• Implement scalable model serving and vector pipelines.
• Collaborate with AI/ML teams to accelerate GenAI adoption.

Skills

LLMs

RAG

Embeddings

LangChain

LlamaIndex

Vector DBs

vLLM

Triton

APIs

CrewAI

Education

Bachelor's or higher in CS

Tools

FAISS

Pinecone

Triton

Job description

The Role

The AI Engineer is responsible for building and scaling enterprise-grade Generative AI platforms that enable rapid development and deployment of LLM-powered applications across the organization. This role focuses on developing reusable GenAI infrastructure including RAG pipelines, vector databases, model serving layers, and agent orchestration frameworks.

Job Description

Key Responsibilities

The Role

The AI Engineer is responsible for building and scaling enterprise-grade Generative AI platforms that enable rapid development and deployment of LLM-powered applications across the organization. This role focuses on developing reusable GenAI infrastructure including RAG pipelines, vector databases, model serving layers, and agent orchestration frameworks.

Key Responsibilities

GenAI Platform Development

• Build and maintain RAG pipelines and LLM orchestration frameworks
• Develop reusable GenAI services and APIs
• Enable multi-agent and agentic workflows

Infrastructure & Systems

• Implement scalable model serving infrastructure (vLLM, Triton, APIs)
• Manage vector databases and embedding pipelines
• Optimize performance and cost of LLM systems

Platform Enablement

• Provide reusable building blocks for AI teams
• Enable rapid experimentation and deployment
• Collaborate with AI/ML teams to accelerate GenAI adoption

Innovation

• Evaluate emerging GenAI tools and frameworks
• Drive adoption of best practices in LLMOps

Key Requirements

• Bachelor/ MSc / PhD in Computer Science, Mathematics or related field of study
• Ongoing commitment to training and professional development in AIML, Aviation Domain, Cargo handling, Ground Handling milestones, Ground Freight and Food Solutions.
• 3 to 5 years in AI engineering / backend systems
• Strong expertise in: LLMs, RAG, embeddings, LangChain / LlamaIndex, CrewAI, Vector DBs (FAISS, Pinecone)