GenAI Engineer - Flexible AI & Data Consulting

Ernst & Young Advisory Services Sdn Bhd; Singapore; On-site; SGD 90,000 - 150,000; Full time

Benefits offered by this job

Continuous learning

Flexible working arrangements

Diverse and inclusive culture

Transformative leadership

Job summary

EY DnA is seeking Junior AI Engineers to join the AI & Data Technology Consulting team in Asia-Pacific. You will design and deploy intelligent GenAI-based applications, integrate with cloud data pipelines, and collaborate with cross-functional teams to translate business requirements into scalable AI solutions.

The role involves rapid prototyping, PoCs, and experiments in AI agent frameworks, with emphasis on production-grade coding practices and DevOps readiness.

Qualifications

• Min bachelor’s degree in computer science, Mathematics, Engineering, Statistics, or a related field.
• At least 1 year of experience with NLP, ML, or Generative AI, specifically with Large Language Models (LLMs).
• Proficiency in Python and other applicable full-stack programming languages.

Responsibilities

• Design and deploy AI-powered workflows with GenAI models and LLMs.
• Develop NLP and predictive models to derive insights from data.
• Collaborate with cross-functional teams to translate business needs into GenAI solutions.
• Prototype, PoCs and experiments in AI agent frameworks (Lang frameworks).
• Ensure code quality and deployment readiness with DevOps practices.

Skills

NLP

Machine Learning

Generative AI

Data Transformation

Scripting

Project delivery

Communication

Education

Bachelor's degree in Computer Science or related

Tools

Docker

Azure

AWS

GCP

Lang Framework

LangChain

LangSmith

Job description

EY DnA is seeking Junior AI Engineers to join the AI & Data Technology Consulting team in Asia-Pacific. You will design and deploy intelligent GenAI-based applications, integrate with cloud data pipelines, and collaborate with cross-functional teams to translate business requirements into scalable AI solutions.

The role involves rapid prototyping, PoCs, and experiments in AI agent frameworks, with emphasis on production-grade coding practices and DevOps readiness.