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Open nowPosted today

LLM, GenAI Engineer

MyCareersFuture97,045 open roles

Pay
SGD 3,000 – SGD 5,000 a month
Where
Central, Singapore
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Your applicationOpen nowLLM, GenAI EngineerMyCareersFuture · Central, Singapore

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The clock on this job

Early applications get read.

8.1% of postings close within 7 days. Measured by our own scanner across the market. MyCareersFuture postings stay open a median of 3 days.

Share of postings closed within
  1. 1.7%1 day
  2. 3.6%3 days
  3. 8.1%7 days
  4. 15.0%14 days
  5. 34.0%30 days
This job: posted today

MyCareersFuture median: 3 days open

The posting

Location: Singapore Work Mode: Onsite Employment Type: Full-time Experience Level: Junior–Mid

Role Overview

We are looking for an AI & Data Engineer with hands-onexperience in Large Language Models, GenAI application development, andcloud-based data engineering. The candidate should be self-driven, curious, andcomfortable independently building end-to-end solutions, from data ingestionand preparation to LLM integration and deployment.

Key Responsibilities

  • Design, build, and enhance LLM-driven applications and frameworks.
  • Implement Retrieval-Augmented Generation, AI agents, and intelligent workflows.
  • Work with LLM tooling and runtimes such as Llama.cpp, Ollama, and similar ecosystems.
  • Build data ingestion, transformation, and ETL/ELT pipelines for structured and unstructured data.
  • Work with cloud data platforms such as Microsoft Fabric, OneLake, Lakehouse, or equivalent technologies.
  • Prepare and process data for AI applications using Python, SQL, Spark, or PySpark.
  • Develop and maintain backend services and APIs using Python.
  • Integrate LLM applications with databases, vector stores, APIs, and enterprise data sources.
  • Research, prototype, and evaluate emerging AI models, frameworks, and data technologies.
  • Continuously improve solution accuracy, performance, scalability, and usability.

Required Skills & Qualifications

  • Strong understanding of LLMs and GenAI applications.
  • Knowledge of RAG, embeddings, vector search, and agentic workflows.
  • Familiarity with LLM frameworks and tooling such as Llama.cpp, Ollama, LangChain, LangGraph, Semantic Kernel, or equivalent.
  • Proficiency in Python and SQL.
  • Understanding of data engineering concepts, including ETL/ELT, data pipelines, data modelling, and data quality.
  • Exposure to Microsoft Fabric, OneLake, Lakehouse, Azure Data Factory, Databricks, or an equivalent cloud data platform.
  • Familiarity with REST APIs, databases, and Git.
  • Ability to independently translate ideas into working technical solutions.
  • Academic background in Artificial Intelligence, Computer Science, Data Engineering, or a related discipline.

Nice to Have

  • Experience running or deploying LLMs locally, on servers, or in cloud environments.
  • Exposure to vector databases, semantic search, and enterprise knowledge retrieval.
  • Knowledge of prompt engineering and LLM evaluation techniques.
  • Experience with Spark, PySpark, Dataflows, or cloud-based data pipelines.
  • Familiarity with Docker, CI/CD, Azure OpenAI, Azure AI Search, or other cloud AI services.
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