System Design & Cloud: Deploy scalable code on cloud environments (AWS/GCP), containerizing services with Docker and maintaining automated CI/CD pipelines.
Based on Southeast Asia business scenarios and Agent applications, participate in designing AI business implementation scenarios to help improve business efficiency and solve business pain points.
Key Responsibilities: Delivery & Transformation: Owns end-to-end technical delivery of complex B2B commerce and customer portal transformation programme - from detailed design through build, migration, cutover, and hypercare. Manages delivery risk, sequencing, and dependencies across squads. Data: Engineers data-intensive solutions and integration flows across enterprise systems. Builds secure, governed, and interoperable data pipelines with strong quality, lineage, and observability.
Personalize each guest experience by using the guests names where known. Acknowledge each special occasion where known. Pass on the relevant guest information to the Captains and Server Attendants.
Act as a full stack "seed" within your team — champion full stack practices, mentor peers, and help scale AI-augmented development across the organization
Act as a full stack "seed" within your team — champion full stack practices, mentor peers, and help scale AI-augmented development across the organization
Prepare architecture and design documents outlining key technical decisions, frameworks, and solution approaches, providing clear guidance to both technical and non-technical stakeholders.
You manage data integrity through SQL and database validation, and leverage AI technologies to enhance development efficiency, automation, and intelligent lending capabilities. You collaborate closely with business, operations, and regulatory stakeholders while ensuring proper documentation, communication, and audit traceability.
Act as a full stack "seed learner" within the team — absorb full stack practices, contribute ideas, and grow into an autonomously delivering full stack engineer
Build production AI systems. Create agents that use tools and customer context to complete real business workflows, learn through feedback loops and long-term memory, and become more useful over time, supported by practical evaluation and observability.
Contribute to cloud infrastructure, CI/CD pipelines, observability and deployment practices across Azure and AWS environments while working closely with Product, UX and Engineering teams to solve customer problems.