AI Engineer

Confirmed live in the last 24 hours

SimplifyNext

Singapore

On-site

Posted April 8, 2026

Job Description

SimplifyNext is a fast-growing consulting and technology firm founded by veterans from top-tier consulting companies, focused on AI, Automation, and Application Platforms. Our mission is to drive business transformation across industries by combining strategic insight with deep technical expertise.

We work with leading enterprises and public sector organisations across Singapore and the Asia Pacific region to design, build, and operate scalable digital and automation platforms — delivering impactful transformations for global and local organisations alike.

Built as an agile practice, we mentor and grow the next generation of consulting and technology experts. We invest heavily in structured training and enablement programmes that help our teams expand across Intelligent Automation, Test Automation, AI-powered workflows, and Agentic AI solutions.

Recognised as one of the fastest-growing companies in Singapore and Asia Pacific, SimplifyNext is positioned as one of the most credible and ambitious digital transformation teams in the region.

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.

What You’ll Do

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.
Support deployment of AI models on cloud platforms (AWS/GCP/Azure) or containerised environments.
Monitor performance and support continuous improvement post-deployment.

Collaboration & Consulting Exposure

Work with functional SMEs to understand business problems and AI opportunities.
Translate complex concepts into simple, understandable terms for non-technical audiences.
Participate in workshops, demos, and client discussions as part of project teams.

pythongorustawsgcpazuremachine learningaiiosdata