AI Engineer (Graduate)

About the role

SimplifyNext is a Singapore-headquartered digital engineering firm, with offices in Thailand and Malaysia, working across three converged areas: agentic AI, AI-enabled application modernisation, and intelligent automation.

We bring strong business process consulting together with deep technology skills and modern delivery practices – product-centric, agile and AI-assisted. We build bespoke applications and AI systems, and we go deep on the platforms our clients run on, including Microsoft, AWS, ServiceNow, Databricks and UiPath. That combination of engineering depth and platform depth is what our clients come to us for.

We build and modernise the systems people depend on daily. Our 300+ practitioners are multi-disciplinary by design – business consultants, software engineers, architects, AI engineers and designers working on the same delivery, not handing off between silos. We focus on delivering outcomes for clients, building strong careers for our people, and staying ahead of the technology curve. We hire because we are growing.

Work you’ll do

As an AI Engineer at SimplifyNext, you will be part of a hands-on engineering team building real-world AI and machine learning solutions that create meaningful impact for clients across ASEAN. You will work closely with consultants, architects, and domain experts to translate business problems into deployable AI models, generative AI workflows, and intelligent automation components.

You will have the opportunity to experiment with modern AI frameworks, build prototypes, fine-tune models, and implement AI capabilities end-to-end—from data preparation to deployment. This role is designed for fresh graduates who want to build, break, learn, and innovate within a supportive environment grounded in consulting excellence and deep engineering capability.

Your responsibilities would include but not limited to:

AI & Machine Learning Development

· Build and train machine learning models using Python and modern ML frameworks

· Experiment with generative AI technologies (LLMs, embeddings, prompt engineering, RAG, agentic workflows)

· Support fine-tuning, optimisation, and evaluation of AI models

· Develop reusable AI components and microservices

Data Engineering & Preparation

· Collect, clean, and transform datasets for training and inference

· Perform exploratory data analysis to uncover patterns and insights

· Document data assumptions, limitations, and preprocessing logic

Solution Engineering

· Contribute to AI solution design, model selection, architecture discussions, and implementation approaches

· Integrate AI models into applications, APIs, and automation workflows

· Build proof-of-concepts (POCs) and accelerate client adoption of AI

Testing, Deployment & Delivery

· Conduct model validation, scenario testing, and UAT with internal and client stakeholders