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1-4 Years
SGD 4,000 - 5,000 per month
  • Posted 3 hours ago
  • Be among the first 10 applicants

Job Description

Key Responsibilities

  • Work closely with management and business users to identify high-value AI use cases and translate business requirements into practical AI solutions.

  • Design, develop and deploy end-to-end AI applications using LLMs, Retrieval-Augmented Generation (RAG), AI agents and machine learning where appropriate.

  • Build AI solutions that integrate with our ERP system, databases, APIs and other enterprise applications.

  • Develop intelligent document-processing solutions for business and engineering documents such as drawings, BOQs, quotations, invoices, timesheets, forms and project documentation.

  • Build enterprise knowledge-search and RAG applications using internal company data and documents.

  • Develop AI agents and automated workflows that can retrieve information, analyse data and support business processes.

  • Build and manage data pipelines required for AI applications.

  • Lead AI proofs-of-concept and pilots and convert successful solutions into reliable production applications.

  • Implement proper AI evaluation, monitoring, version control, security, access control and cost management.

  • Ensure AI solutions comply with data privacy, cybersecurity and responsible AI requirements.

  • Evaluate different AI models, platforms and technologies and recommend appropriate build-vs-buy approaches.

  • Establish internal AI development standards, documentation and best practices.

  • Train and support employees in adopting newly developed AI solutions.

  • Track the business impact of AI projects through measurable outcomes such as productivity improvement, time savings, cost reduction, accuracy and user adoption.

Requirements

  • Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Engineering or a related discipline, or equivalent practical experience.

  • Preferably 3-5 years of relevant experience in software engineering, AI/ML engineering, data engineering or solutions development.

  • Strong programming skills in Python.

  • Hands-on experience developing applications using LLM platforms and APIs, such as OpenAI, Claude or open-source models.

  • Practical experience with RAG, embeddings, vector databases and AI agents.

  • Experience with REST APIs, system integration, databases and data pipelines.

  • Good understanding of machine-learning and software-engineering fundamentals.

  • Experience deploying applications on cloud platforms such as Microsoft Azure, AWS or GCP.

  • Familiarity with Git, CI/CD, monitoring, evaluation and MLOps/LLMOps.

  • Ability to take an AI solution from idea → prototype → pilot → production deployment.

  • Strong problem-solving and analytical skills.

  • Able to communicate effectively with both technical and non-technical stakeholders.

Good to Have

Experience in any of the following would be an advantage:

  • Microsoft Azure / Azure AI

  • Microsoft Power Platform / Power Automate / Power BI

  • OCR and intelligent document processing

  • ERP or enterprise-system integration

  • SQL and enterprise databases

  • Agentic AI and workflow automation

  • AI governance and cybersecurity

  • Construction, engineering, manufacturing or other project-based industries

Industry experience is an advantage but not mandatory. We value strong technical capability, problem-solving skills and the ability to understand business processes.

What You Will Get to Work On

This is not purely a research or model-training position. You will have the opportunity to build real AI applications that are used in day-to-day business operations.

You will work directly with business users, management and external technology partners and play an important role in developing Addcel's long-term in-house AI and digital capabilities.

We are looking for someone who is curious, hands-on and excited about using AI to solve real business and engineering problems.

More Info

Job Type:
Industry:
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Key Skills

RAG embeddings

data pipelines

LLMOps

LLM platforms and APIs

vector databases

AI agents

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