Senior Site Reliability Engineer
At a glance
Senior Site Reliability role at Aliz. Jakarta · full-time.
Pay not stated Site Reliability Engineer salary
devopsroles summary, based on the employer's posting.
What you'll do
- Build pre-release checks, staged rollouts and recovery paths so AI-assisted changes reach production safely
- Set reliability targets and use service indicators and error budgets to balance delivery pace with stability
- Create reusable AI-agent workflows for alert triage, incident investigation, maintenance and reporting, with checks and human approval
- Improve logs, metrics, traces and alerts, then turn incident findings into runbooks, tests and safeguards
- Extend Terraform and delivery tools while improving GCP networking, access controls and capacity management
What you bring
- At least six years in SRE, production engineering or infrastructure-heavy backend work, with direct responsibility for live systems
- Strong hands-on GCP experience, including Cloud Run, networking and IAM; cloud skills are assessed in interviews
- You can use Terraform and CI/CD practices to keep infrastructure consistent and releases safe
- You build maintainable operational tools in Go, Python or a comparable language, and can troubleshoot systems through to verified fixes
- You have led production incident investigations and can critically test and validate AI coding agents’ output
Who this fits
This suits a senior engineer who wants hands-on ownership of production reliability and is motivated to make AI-assisted engineering faster and safer. AI coding agents are expected in day-to-day work, and you’ll need strong written English for asynchronous collaboration with a distributed team. The role is based in Jakarta, Indonesia.
From the employer
The Role
Help Rabbit build and ship faster with AI — safely, securely and reliably.
Rabbit runs automated cost optimization across enterprise Google Cloud environments. When we change a customer's BigQuery reservations or rightsize their GKE clusters, those changes need to be correct and dependable. Reliability is central to the trust customers place in our product.
Our foundation is already in place: logging, alerting, automated deployment and Terraform-managed infrastructure. Your mission is to evolve that foundation for an AI-accelerated engineering team: turn faster implementation into faster, dependable delivery through automated validation, safe releases and rapid feedback.
You'll apply proven SRE practices — SLOs, observability, incident response and deployment safety — to AI-assisted development and agent-driven workflows. The goal is to increase how quickly the team can deliver verified improvements, while controlling production risk and reducing manual operational work.
What You'll Do
- Make AI-assisted delivery faster and safer. Build automated validation, progressive rollout and recovery mechanisms that let engineers and agents move quickly with clear checks before and after changes reach production.
- Make reliability measurable. Define and operationalize SLOs, SLIs and error budgets, and use them to guide practical decisions about delivery speed, stability and reliability work.
- Automate workflows with AI agents. Identify repetitive operational work and build reusable agent-driven workflows for alert triage, incident investigation, routine maintenance and reporting. Add verification and human approval where needed, and measure the reduction in manual effort.
- Improve observability and feedback. Evolve logging, metrics, tracing and alerting so failures are detected early and changes can be traced, investigated and verified.
- Turn incidents into lasting improvements. Improve runbooks, investigation and blameless postmortems, and translate recurring problems into tests, safeguards and automation.
- Keep infrastructure reproducible. Extend our Terraform and delivery tooling so environments remain consistent and changes stay reviewable as the platform grows.
- Improve GCP reliability and efficiency. Strengthen our cloud infrastructure, networking, access controls and capacity management, balancing performance, reliability and cost.
- Use AI to accelerate reliability engineering itself. Build maintainable tooling in Go, Python or a comparable language, and use agents to accelerate investigation, implementation, testing and documentation while verifying their outputs.
How We Work — AI-First, Agentic by Default
AI-assisted engineering is an expectation of this role, not an optional experiment. Claude Code, Cursor and agent-driven workflows are part of how we work, including infrastructure and reliability engineering.
We want someone who actively looks for ways to increase engineering speed with AI and makes those improvements safe to repeat. That means shorter feedback loops, automated checks, traceable changes and recovery paths — not simply generating more code.
You remain accountable for engineering judgment: what to automate, how to verify it, when human approval is needed and when a change should be stopped or rolled back. Success means faster delivery of reliable improvements, less repetitive work and a platform the team can trust.
What You'll Bring
Must-have
- 6+ years in SRE, production engineering or infrastructure-heavy backend roles, with hands-on ownership of production systems.
- Strong production GCP experience, including Cloud Run, networking and IAM. Hands-on Google Cloud experience is required and will be assessed during the interview process.
- Infrastructure-as-code fluency with Terraform, plus solid experience in CI/CD and deployment safety.
- Strong observability and troubleshooting skills: you can make systems debuggable, identify root causes and verify that a fix works.
- Coding ability in Go, Python or a comparable language, with experience building maintainable operational tooling.
- Experience leading production incident investigation and driving follow-up improvements that prevent recurrence.
- Practical fluency with AI coding agents and the ability to critically review, test and validate their work. You are motivated to make AI-assisted engineering faster and more dependable.
- Strong written English and the discipline to collaborate asynchronously with a distributed team.
Nice to have
- Kubernetes / GKE experience, including deploying, operating, debugging and scaling containerized services.
- Hands-on Datadog experience, including dashboards, monitors, logs, APM and distributed tracing.
- Experience improving delivery speed and safety through progressive delivery, policy-as-code and automated rollback.
- GCP cost management or FinOps experience.
- Security experience is a plus.
Why This Role
- Shape how an AI-first engineering team scales. Build the reliability practices and automation that let Rabbit turn faster development into dependable customer outcomes.
- Work on systems with real customer impact. Rabbit operates inside enterprise GCP environments, where reliability and security directly affect customer trust.
- Own meaningful improvements. Work in a small team with short decision paths and end-to-end ownership, supported by appropriate review and production safeguards.
- Use AI as an engineering multiplier. Apply agentic tools to infrastructure, delivery and operations, and help define how we measure and improve their impact.
About Aliz
Aliz was founded by a group of driven software engineers with one vision in mind: Build a human-centered company to solve exciting business challenges with cutting-edge technologies all around the globe.
We are a proud Google Cloud Partner with specializations in Generative AI, Infrastructure, Data Analytics, Cloud Migration, and Machine Learning - we deliver solutions, off the shelf, or custom-built on GCP using an agile, holistic approach. Our team includes engineers, industry experts, and digital professionals who ensure our clients are ready to face the challenges of the ever-changing digital world.
Life has been pretty exciting at Aliz recently (here's proof). Since winning Google Cloud’s Breakthrough Partner of the Year in APAC, we’ve continued to grow our team and expertise and were more recently recognized with the Partner of the Year Award in the Alps and the Google Cloud Generative AI Specialization. We have over 100 people working from our offices in Europe or Asia, and we're still counting!
You couldn’t pick a better time to join this world-class team of GCP experts.