AI Engineer

JOB DESCRIPTION

As an AI Engineer, you will use Generative AI techniques complemented with data science modelling to develop models and products that support various business 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.

Your roles and responsibilities include:

• 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 the client's portfolio of deployed AI applications and data science models, including its in-house agentic platform.
• Researching emerging AI/data science techniques and identifying relevant ones for the organisation to explore and adopt (e.g. Agentic AI, LLM, Predictive Modelling, Fraud/Anomaly Detection, Text Analytics, Customer Segmentation).
• Data wrangling and analysis, including 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.

To perform this role, you must have/be:

• Minimum of a Bachelor's Degree in Computer Science, Computer Engineering, Machine Learning, Data Science, AI or related disciplines.
• Experience in cloud platforms and services, preferably 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.
• Experience with harness engineering, context engineering techniques and prompt optimization strategies.
• 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), RESTful API development, and frontend technologies (e.g. React, Vue.js, HTML/CSS, TypeScript).
• Experience with Docker/Kubernetes for deploying production-grade applications.
• Proficient in Git, SQL and modern programming languages (e.g. TypeScript, C#).
• Proficient in Business Intelligence tools (e.g. Tableau, Qlik, MS Power BI, MicroStrategy).
• Strong presentation skills and ability to explain technical concepts clearly to a non-technical audience.