AI Engineer

RECRUIT EXPRESS PTE LTD; Singapore; On-site; SGD 100,000 - 140,000; Full time

Job summary

RECRUIT EXPRESS PTE LTD is seeking a GenAI engineer to develop and deploy AI-powered applications, including chatbots and document analyzers. You will fine-tune LLMs on specialized data and implement RAG pipelines and multi-step reasoning workflows.

Responsibilities include integrating GenAI pipelines into production with ML Ops tools, building scalable inference APIs, and ensuring prompt engineering, vector database usage, and security practices are in place.

Qualifications

• Experience building GenAI systems and end-to-end AI apps.
• Ability to fine-tune and evaluate LLMs with custom datasets.
• Knowledge of RAG, vector search, and orchestration frameworks.

Responsibilities

• Develop and deploy GenAI-powered apps such as chatbots and document analyzers.
• Fine-tune and evaluate LLMs using domain-specific datasets.
• Implement RAG, agents, and multi-step reasoning workflows.
• Integrate GenAI pipelines into production using ML Ops tools.
• Build and monitor inference APIs with performance and cost in mind.
• Apply prompt engineering and vector databases for robust solutions.
• Ensure model explainability, bias mitigation, and security considerations.

Skills

LLM development

Fine-tuning

RAG pipelines

ML Ops

Prompt engineering

Vector databases

Security

Explainability

Education

Bachelor's in CS/AI

Tools

MLflow

Azure ML

Databricks

Job description

Job Description:

• Develop and deploy applications that use LLMs (e.g., chatbots, document analyzers, code generators).
• Fine-tune and evaluate LLMs using custom datasets.
• Implement RAG (retrieval-augmented generation), agents, or multi-step reasoning workflows.
• Integrate GenAI pipelines into production systems using ML Ops tools (e.g., ML flow, Azure ML, Databricks).
• Build and monitor inference APIs with performance and cost considerations.
• Apply prompt engineering, vector databases, and orchestration frameworks.
• Ensure responsible AI practices, including model explainability, bias mitigation, and security