AI Engineer
- Compensation
- SGD 3.6K–SGD 4.2K / mo
- Location
- Singapore
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- Bachelor's Degree, Master's Degree or equivalent practical experience in Computer Science, Information Technology, Engineering, Data Science, or related disciplines.
- 3+ years of professional software development, AI engineering, automation engineering, or related experience.
- Strong hands-on Python development experience.
- Demonstrated experience building and deploying AI-enabled solutions using LLMs or Generative AI technologies.
- Experience integrating foundation model APIs such as:
- OpenAI
- Azure OpenAI
- Anthropic Claude
- Google Gemini
- Amazon Bedrock
- Hugging Face
- Equivalent platforms
- Strong understanding of:
- Prompt engineering
- Context engineering
- LLM fundamentals
- Embeddings
- Vector search
- Retrieval-Augmented Generation (RAG)
- Experience designing and implementing AI assistants, copilots, chatbots, agentic workflows, or intelligent automation solutions.
- Familiarity with software engineering best practices including Git, code reviews, testing, and Agile delivery methodologies.
- Strong problem-solving and analytical thinking skills.
- Excellent communication and stakeholder engagement skills.
Full description
AI Engineer (LLM, GenAI & Agentic Systems)The ideal candidate is an AI engineer who can build and deploy real-world LLM and GenAI solutions. Experience delivering AI applications, agentic systems, RAG solutions, and AI-assisted engineering practices will be weighted more heavily than frontend framework expertise
About the Role
We are seeking a talented AI Software Engineer (LLM, GenAI & Agentic Systems) to join our growing AI Engineering team. This role focuses on designing, building, and deploying production-grade AI solutions that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic workflows, and AI-assisted software engineering practices.
You will work closely with solution architects, product teams, data scientists, and clients to transform AI concepts into scalable, secure, and business-ready applications. Beyond writing high-quality software, you will play a key role in shaping how AI technologies are applied responsibly and effectively across enterprise environments.
Key ResponsibilitiesAI Solution Development
- Design, develop, test, and deploy AI-enabled applications using Large Language Models (LLMs), Generative AI technologies, and intelligent automation frameworks.
- Integrate foundation models and AI services such as OpenAI, Azure OpenAI, Anthropic Claude, Amazon Bedrock, Google Gemini, Vertex AI, or equivalent platforms.
- Develop AI-powered solutions including:
- Enterprise chatbots and virtual assistants
- Retrieval-Augmented Generation (RAG) applications
- Intelligent document processing solutions
- Knowledge management assistants
- AI copilots and task automation agents
- Multi-agent and agentic workflow systems
- Translate business requirements into scalable AI solution architectures.
- Partner with stakeholders to prototype, demonstrate, and productionize AI capabilities.
Agentic Systems & Intelligent Automation
- Design and implement agent-based architectures and workflow orchestration solutions.
- Build systems that leverage tool/function calling, memory management, context engineering, and task planning.
- Develop AI workflows that interact with enterprise applications, APIs, and knowledge repositories.
- Evaluate and optimize agent performance for accuracy, reliability, latency, and operational efficiency.
- Implement suitable safeguards and human-in-the-loop controls for critical business processes.
Retrieval-Augmented Generation (RAG) & Knowledge Systems
- Design and implement RAG architectures using embeddings, semantic search, and retrieval pipelines.
- Develop ingestion, indexing, retrieval, and ranking workflows for enterprise knowledge repositories.