GenAI Engineer

2 weeks ago

Bangkok, Bangkok, Thailand AIA Thailand Full time

Job Summary:

Design, develop, and deploy cutting-edge GenAI solutions leveraging large language models, retrieval-augmented generation, and prompt engineering to solve complex business problems in life insurance. You'll work across the full stack—from model selection and fine-tuning to application development and production deployment.

Key Responsibilities:

  • Design and implement GenAI solutions using LLMs and other techs
  • Build RAG (Retrieval-Augmented Generation) systems with vector databases
  • Develop and optimize prompts for accuracy, reliability, and cost-efficiency
  • Implement fine-tuning and model customization when needed
  • Build evaluation frameworks to test model performance, bias, and safety
  • Implement guardrails, safety checks, and content filtering
  • Stay current with rapidly evolving GenAI landscape and best practices
  • Document technical approaches and share knowledge with the team

Qualifications:

  • 3+ years software engineering experience with production systems
  • 1+ years hands-on experience with LLMs and GenAI applications
  • Strong Python programming skills (FastAPI, LangChain, LlamaIndex, or similar)
  • Experience with OpenAI, or other LLM APIs
  • Understanding of RAG architectures and vector databases
  • Experience with prompt engineering and optimization
  • Familiarity with ML fundamentals
  • Experience with cloud platforms (Azure, AWS, or GCP)
  • Strong problem-solving and debugging skills
  • Bachelor's degree in Computer Science, Engineering, or related field

Preferred Qualifications:

  • Experience with embedding models and semantic search
  • Knowledge of transformer architectures and attention mechanisms
  • Experience with MLOps tools and practices
  • Experience with front-end development (React, Vue, etc.)

Key Technical Skills:

  • Python, REST APIs, JSON
  • LLM frameworks: LangChain, LlamaIndex
  • Vector databases and semantic search
  • Prompt engineering and chain-of-thought techniques
  • Model evaluation and testing frameworks
  • Git, Docker, CI/CD basics

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