Senior Backend Engineer

Job Description

Traveloka is Southeast Asia's leading travel and lifestyle super-app. We connect tens of millions of travellers across the region with flights, hotels, experiences, financial services, and more — all from a single platform. Since our founding in 2012, we have expanded to eleven markets, processed billions of dollars in transactions, and built one of the most recognised consumer brands in the region.

We move fast because the region demands it. Southeast Asia is young, mobile-first, and growing faster than almost anywhere else on earth. We are not transplanting a Western playbook — we are writing a new one, from scratch, for a market that does not look like anywhere else — and we are calling for people who want to be part of that.

About The Team

We are the engineers behind the part of the trip people actually remember. Travel Activities powers Traveloka's experiences business — attraction tickets, guided tours, cruises, and local experiences across Southeast Asia and beyond. You will build the systems that turn a fragmented, messy supply landscape into something a traveller books in seconds: search and inventory that span thousands of operators, booking flows tuned for eleven markets, and apps that work on the phone in someone's hand at the gate of a theme park.

Whether you write backend, frontend, or mobile, you ship to millions and see the impact in real bookings. We move fast, lean hard into AI to scale what we build, and partner with world-class brands. If you want product rigour and commercial creativity in equal measure — not a Western playbook, but a new one written for this region — this is your team.

About The Job

As a Senior Backend Engineer on Traveloka's Travel Activities team, you are a technical expert who designs the systems your area is built on and sets the technical direction others build against, with direct impact on the domain's results.

• Design and ship multi-service systems for Travel Activities, owning the system-level consistency, latency, and cost tradeoffs, and lead deep architecture work that spans services and teams, untangling complex trade-offs across performance, cost, and correctness
• Decompose an ambiguous product problem into a service architecture, API contracts, and a plan others can execute
• Set the technical bar through rigorous, constructive review, and shape the APIs other teams build against cleanly
• Mentor junior and mid-level engineers through review and pairing, growing their judgment without managing them
• Act as senior on-call authority on your systems, killing whole classes of incidents through durable design, not patching
• Influence the engineering roadmap with technical proposals that shape what the wider team builds next
• Direct how the team uses AI tools in its workflow, judging where they speed delivery and where they introduce risk

Job Requirements

• You have at least 8 years of backend engineering — and your judgment on system design now comes from having built and operated systems, however you got there.
• You have designed a system that spans multiple services from scratch, and it has held up in production.
• You own the consistency, latency, and cost tradeoffs at the system level, not just within one service.
• You can take an ambiguous product problem and decompose it into a clean service architecture.
• You produce clear API contracts and a delivery plan others can execute.
• You have owned a system through real scale growth or a reliability turnaround.
• You can point to the architectural decisions that made it hold.
• You set the technical bar for an area through rigorous, constructive review, and engineers around you get better because of how you review and design.
• You have a degree in Computer Science or a related field, or equivalent depth from real-world engineering.
• You mentor junior to middle-level engineers deliberately — you grow their judgment, not just unblock their tickets.
• You partner with Product to map technical dependencies and shape APIs and integrations that other teams build against cleanly.
• You set how your team uses AI tools in its workflow.
• You can judge where they accelerate delivery and where they introduce risk worth guarding against.