Agoda

Agoda

Senior GenAI/MLOps Engineer - Bangkok-based (Full Relocation Package Provided)

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🌍Bangkok
16h ago
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Job Description

Hybrid

About Agoda 

Agoda is an online travel booking platform for accommodations, flights, and more. We build and deploy cutting-edge technology that connects travelers with a global network of 4.7M hotels and holiday properties worldwide, plus flights, activities, and more. Based in Asia and part of Booking Holdings, our 7,100+ employees representing 95+ nationalities in 27 markets foster a work environment rich in diversity, creativity, and collaboration. We innovate through a culture of experimentation and ownership, enhancing the ability for our customers to experience the world.

Our Purpose - Bridging the World Through Travel 

We believe travel allows people to enjoy, learn and experience more of the amazing world we live in. It brings individuals and cultures closer together, fostering empathy, understanding and happiness.
We are a skillful, driven and diverse team from across the globe, united by a passion to make an impact. Harnessing our innovative technologies and strong partnerships, we aim to make travel easy and rewarding for everyone.

LLM Platform at Agoda

Agoda’s LLMOps Platform is at the forefront of enabling scalable, secure, and efficient deployment of Large Language Models (LLMs) and generative AI solutions. Built on robust cloud and on-premises infrastructure, our platform empowers teams to experiment, deploy, and monitor LLM-powered applications with confidence and agility.

Our LLMOps team bridges the gap between advanced AI research and real-world production systems, ensuring that LLMs are delivered reliably, responsibly, and at scale. We focus on best practices in model lifecycle management, data privacy, prompt engineering, and continuous improvement to help our users unlock the full potential of generative AI.

 

In This Role, You’ll Get to: 

  • Lead the design, development, and implementation of LLMOps solutions for deploying, monitoring, and managing large language models and generative AI systems
  • Collaborate with data scientists, ML engineers, and product teams to build scalable pipelines for LLM fine-tuning, evaluation, and inference
  • Develop and maintain tools for prompt management, versioning, and automated evaluation of LLM outputs
  • Ensure responsible AI practices by integrating data anonymization, bias detection, and compliance monitoring into LLM workflows
  • Develop and maintain monitoring and management tools to ensure the reliability and performance of our on-premises and cloud machine learning platform.
  • Work with stakeholders across the organization to understand their generative AI needs and deliver LLMOps solutions that drive business impact
  • Stay up-to-date with the latest trends and technologies in LLMOps, generative AI, and responsible AI, and share your knowledge to keep the team at the cutting edge
  • Mentor junior team members  and help them grow their skills and expertise in LLMOps
  • Troubleshoot and resolve issues related to LLM deployment, scaling, and performance

What You’ll Need to Succeed:

  • 5+ years of experience in LLMOps, MLOps, Software Engineering, or a related field
  • Strong programming skills in a modern language (Python, Kotlin, Scala, Java, etc.)
  • Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams
  • Commitment to code quality, simplicity, and performance

It’s Great if you have:  

  • Experience with LLMOps platforms and tools (e.g., Hugging Face, LangChain, Ray, MLFlow, Kubeflow)
  • Familiarity with prompt engineering, retrieval-augmented generation (RAG), and LLM evaluation frameworks
  • Experience with data privacy, PII anonymization, and responsible AI practices
  • Strong knowledge of containerization and orchestration (Docker, Kubernetes)
  • Experience with DevOps, CI/CD, and scalable API development for LLM serving
  • Passion for the engineering challenges of generative AI and scaling LLM solutions
  • Experience designing and building LLMOps infrastructure, including data pipelines, model management, and monitoring tools
  • Deep understanding of LLM architectures (e.g., GPT, Llama) and experience with model fine-tuning, evaluation, and deployment

Benefits 

  • Flexible hybrid work arrangement with the option to work remotely for part of the year 
  • Generous annual leave, sick leave, and public holidays 
  • Exclusive accommodation discounts for personal travel 
  • Annual allowance for wellness, learning, fitness, and travel experiences 
  • Opportunities for career growth through training, certifications, and internal promotions 
  • Competitive compensation and comprehensive health benefits 

Relocation Package (for employee and family): 

  • Full visa sponsorship for employees, spouse, and children 
  • Support for airfare, travel insurance, and temporary accommodation upon arrival 
  • Assistance with moving household goods and pet relocation 

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Equal Opportunity Employer 

At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person’s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.

We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.

 

Disclaimer

We do not accept any terms or conditions, nor do we recognize any agency’s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.

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