[Infra] Staff/Lead Software Engineer – Compute Platform (Bangkok Based, relocation provided)

Agoda · Bangkok, Thailand · по договорённости

Компания
Agoda
Город
Bangkok, Thailand
Зарплата
по договорённости
Уровень
lead
Формат
full_time
Иностранная компания
нанимает русскоязычных

About Agoda

At 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 [NASDAQ: BKNG], 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.

No 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.

Get to Know our Team

The Compute Platform team operates the fleet of bare metal and virtual machines infrastructure that every product at Agoda runs on. As part of the team, you will be contributing to a mission-critical private cloud with over one million cores, spread across hundreds of Kubernetes clusters, OpenStack virtual machines, and bare metal servers across our global data centers.

A core part of the team's roadmap is ACP (Agoda Compute Platform), our in-house, lightweight orchestration stack for dedicated-resource virtual machines on bare metal, alongside broader fleet lifecycle tooling and automation.

The Opportunity

Our Compute Platform team in Bangkok is looking for an experienced Staff/Lead Software Engineer to take technical ownership of ACP and our wider fleet and compute platform. You will be a senior, hands-on individual contributor: someone who can independently design, build, and drive the architecture of large-scale infrastructure systems, while mentoring other engineers and representing the team as a technical point of contact across Agoda's engineering organization.

In This Role, You'll Get to:

Own and evolve the architecture of ACP: the orchestrator, per-host agent, and CLI that manage dedicated-resource virtual machines on bare metal, including compute placement, image management, and network recovery.

Design, build, and operate Agoda's compute and fleet tooling in Go (and Python where relevant), including systems that interface with Kubernetes, OpenStack, and out-of-band hardware management APIs.

Lead medium to large projects across Fleet, Compute Platform, and adjacent teams, with ownership from design through delivery and operation.

Take an active role in System Design Reviews, both within the team and across the wider engineering organization, influencing architecture beyond your own systems.

Use agentic coding tools (for example Claude Code and similar) as a normal part of design, implementation, testing, and review — the way the team works today — and help others use them well without lowering engineering standards.

Troubleshoot product and system issues at scale across multiple global data centers.

Interview and mentor engineers across the team and help raise the hiring bar for compute and fleet roles.

Define and use clear measures for ACP reliability, operational load, and delivery quality, and use them to decide what to build next.

Work with Software Development, Infrastructure Management, and adjacent teams to gather requirements and design scalable, resilient services.

Write the technical documentation and training the team needs to operate and extend ACP.

What You'll Need to Succeed:

10+ years of software engineering, with a strong hands-on background in infrastructure or compute systems (bare metal, virtualization, Kubernetes, and/or OpenStack).

Strong distributed systems development skills in Go; Python is advantageous.

Proven experience owning and evolving distributed systems such as control planes, orchestrators, or agents in production.

Experience with virtualization and bare-metal provisioning at scale.

Practical experience using Kubernetes in production (workloads, API

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