Senior Platform Engineer, Deployment & Progressive Delivery

Grab; Petaling Jaya; On-site; MYR 180,000 - 280,000; Full time

Benefits offered by this job

Term Life Insurance

Medical Insurance

GrabFlex benefits

Parental Leave

Birthday leave

LASA volunteering leave

Grabber Assistance Programme

FlexWork hours

Job summary

Grab, Southeast Asia's leading superapp, seeks a senior platform engineer for its Petaling Jaya, Malaysia office. You will own deployment platform components end to end and extend the model to multi-cluster and multi-region deployments, enabling safe, progressive rollouts across hundreds of services.

Join a team that designs abstractions for ML model serving and ensures durable platform fixes while mentoring engineers and guiding technical direction.

Qualifications

• Production Go (or comparable systems language) experience.
• Strong Kubernetes depth including controllers, reconciliation, and CRDs.
• Experience building or operating deployment/CD systems with progressive delivery.
• Ability to write RFCs and close the design-to-operations loop.
• Direct experience with EKS at scale, Istio, Flagger, Argo Workflows/CD, Helm or OCM.
• Exposure to multi-cluster or multi-region Kubernetes architectures.

Responsibilities

• Manage deployment platform components end to end from RFC to rollout and operation.
• Extend deployment models for multi-deployment placement with Istio orchestration.
• Build and harden progressive-delivery mechanics with canary and blue/green rollouts.
• Design abstractions for heterogeneous ML workloads on the platform.
• Debug cross-system production issues involving deployment, autoscaling, and service mesh.
• Raise engineering bar through design reviews, RFCs, and mentorship.

Skills

Go

Kubernetes depth

RFCs

Multi-cluster

Multi-region

Tools

EKS

Istio

Flagger

Argo

Helm

OCM

Karpenter

KEDA

Job description

Grab, Southeast Asia's leading superapp, seeks a senior platform engineer for its Petaling Jaya, Malaysia office. You will own deployment platform components end to end and extend the model to multi-cluster and multi-region deployments, enabling safe, progressive rollouts across hundreds of services.

Join a team that designs abstractions for ML model serving and ensures durable platform fixes while mentoring engineers and guiding technical direction.