Design and write backend or frontend code to improve the availability, scalability, latency, and efficiency of Grab’s range of services or mobile applications. Participate in both code and design reviews.
Contribute to the development of technical strategies and roadmaps for the Fulfilment domain, aligning with broader team goals.
Oversee end-to-end development of your team’s products, including ownership of the team’s infrastructure using Terraform, building and scaling backend services, designing efficient backend service interactions, and performing root cause analysis investigations.
Engage in Driver app stability investigation, application performance analysis, tuning, and optimisation. Be part of an on-call rotation for your team’s products and services, and participate in post-mortems for any incidents.
Work in a regional organisation with offices across different countries and cultures, facilitating collaboration across these diverse teams. Collaborate with product managers, data analysts, and product designers to implement products and features, and test their impact on business metrics.
Lead junior engineers, fostering a culture and continuous improvement within the team.
Recommend new technologies, frameworks, and tools that can enhance the team’s productivity and the quality of Grab’s services. Drive innovation by researching and prototyping new technologies and approaches to solve complex fulfillment challenges.
Contribute to the broader tech community through knowledge sharing, writing technical blog posts, and participating in relevant conferences or meetups.
Requirements & Skills:
Fluent in English, conscientious, and teamwork, and a positive and optimistic outlook.
8+ years of working experience in mobile application development
Strong computer science fundamentals including data structures, algorithms, multithreading, relational and non-relational databases
Proficient with at least one language commonly used language for backend or frontend development.
Demonstrate an understanding of cloud infrastructure with hands-on experience.
A degree in computer science, software engineering, or related fields
Experience with high-speed distributed computing frameworks like Apache Flink
Experience with Kubernetes, and Dockers.
Experience writing real-time input signals for a Machine learning Model is a big plus.
