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

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 experi...

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.

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.

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, APIs, and how clusters actually behave).
Comfortable using agentic coding tools in day-to-day software development, or able to adopt the team’s workflow quickly. These tools are how we work; they are not a substitute for distributed-systems judgment, code quality, or operational ownership.
Strong understanding of observability for distributed systems: monitoring, alerting, logging, and visualisation at scale.
A track record of leading medium to large technical projects and driving architectural decisions inside a team.
Experience working across team boundaries and learning the internals of adjacent systems, not only your own.
Clear written and verbal English, including design docs, reviews, and cross-team discussion.
Hands-on experience with Kubernetes beyond cluster-user work: controllers, operators, and/or CRDs.
Experience contributing to or maintaining open-source Kubernetes Operators/Controllers.
Experience with configuration management and automation tooling, preferably Ansible and/or AWX.
Experience with out-of-band hardware management APIs (iLO, DRAC) and physical architecture at scale, including building resilient, highly available solutions with no single point of failure.
Experience with CI/CD and GitOps approaches to infrastructure delivery.
Experience working across a large, distributed engineering organization with many stakeholders.

 
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