Technical Product Manager
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("All roles in Bangkok, Thailand"), this listing's salary midpoint is about 90% lower. The offer sits below the benchmark range (€9,260–€13,890). Range-width comparison is limited because one of the salary bands is incomplete. This benchmark is based on 3 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| All roles in Bangkok, Thailand | €9,260/per month | €13,890/per month | €13,890/per month |
| Pay in our data — not quoted in ad (Manager) | €1,158/per month | €1,158/per month | €1,158/per month |
About Agoda\n\nAt Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world. Today, we are part of Booking Holdings, with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.\n\nNo two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you’re ready to begin your best journey and help build travel for the world, join us.\nTechnical Product Manager – ML & LLM Platforms…
Job Details
Responsibilities
- Define and evolve the product vision and roadmap for Agoda’s ML & LLM Ops platforms
- Shape how teams productionize ML models and LLM-powered applications
- Identify platform gaps, scalability constraints, and optimization opportunities
- Drive the evolution of our platform to support AI-native development workflows and coding agents
Requirements
- 5+ years of experience in ML engineering, data science, platform engineering, or a related technical domain
- 2+ years of technical product or program management experience in fast-paced, high-scale environments
- Experience working with ML Ops and/or LLM Ops concepts (model lifecycle, evaluation, monitoring, versioning, deployment pipelines)
Skills & Technologies
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