M01 - AI Engineer

Overview

As an AI Engineer, you will use Generative AI techniques complemented with data science modelling to develop models and products that support a range of divisions across investment promotion, industry development and corporate functions. You will have the opportunity to partner closely with key stakeholders to identify business challenges, translate user needs into technical requirements, and deliver AI and Machine Learning solutions that drive measurable outcomes.

Responsibilities

• Collaborating with business users to understand their key priorities and use cases
• Proposing and developing solutions using data science and/or Generative AI techniques to drive business value
• Working directly on building portfolio of deployed AI applications and data science models, including our in-house agentic platform
• Data wrangling & analysis - preprocessing, cleaning and feature engineering
• Developing backend APIs and services to support AI model deployment and integration
• Building frontend interfaces and user experiences for AI-powered applications
• Reviewing and implementing fixes for reported security vulnerabilities
• Researching emerging AI/data science techniques and identifying relevant ones for EDB to explore and adopt (e.g. Agentic, LLM, Predictive, Fraud/Anomaly Detection, Text Analytics, Customer Segmentation)

Requirements

• Minimum of Bachelor's Degree in Computer Science, Computer Engineering, Machine Learning / Data Science / AI or related disciplines;
• Experience in cloud platform and services preferably in AWS
• Understanding of LLM concepts (e.g. context windows, embeddings, chunking,token management) and architectures (e.g. RAG), including Knowledge of vector databases and embedding techniques
• Understanding of AI agent frameworks and multi-agent systems (e.g. LangChain, LangGraph, DeepAgents)
• Experience with web frameworks and full-stack development, including backend frameworks (e.g. FastAPI, Flask, Express.js) and RESTful API development, and frontend technologies (e.g. React, Vue.js, HTML/CSS, TypeScript)
• Experience in Docker/Kubernetes for deploying production grade applications
• Strong presentation skills and ability to explain technical concepts clearly to a non-technical audience
• Experience with harness engineering, context engineering techniques and prompt optimization strategies
• Proficient in git, SQL, modern programming languages (e.g. typescript, C#)
• Proficient in Business Intelligence tools (e.g. Tableau, Qlik, MS PowerBI, Microstrategy)