Hiredly X Hiring! Full Time Senior Platform Engineer in , Earn up to MYR 12,000 - Ricebowl

As a Senior Platform Engineer, you will play a critical role in building and evolving the core infrastructure that powers SupplyOS, agentic AI platform for enterprise supply chain operations.

You will design, build, and own foundational platform systems that enable multi-agent orchestration, workflow execution, data ingestion, and intelligent memory at scale. Your work will directly support Forward Deployed Engineers (FDEs) in delivering high-impact customer deployments and will shape how SupplyOS operates in production across large enterprises.

This role sits at the intersection of AI systems, distributed infrastructure, and real-world operational constraints. You will be expected to exercise strong technical judgment, build reliable abstractions, and solve hard problems around scalability, performance, and reliability. 

This role is ideal for senior engineers who enjoy owning core systems, raising engineering standards, and building platforms that other teams depend on.

1. Core Platform Architecture & Development

• Design, build, and evolve critical platform components such as API services, workflow engines, multi-agent orchestration systems, RAG infrastructure, and intelligent memory systems.
• Own major subsystems within SupplyOS, including architecture, implementation, testing, and long-term maintainability.
• Ensure platform components are robust, extensible, and production-ready.

2. Enablement of Forward Deployed Engineering

• Identify friction points slowing down FDEs and customer deployments.
• Build abstractions, APIs, and tooling that enable FDEs to move faster and deploy SupplyOS reliably across diverse customer environments.
• Translate real-world deployment learnings into scalable platform capabilities.

3. Technical Excellence & Engineering Standards

• Set and uphold standards for code quality, testing, observability, performance, and reliability across the platform.
• Review designs and code, providing mentorship and technical guidance to other engineers.
• Drive best practices in building and operating AI-driven systems in production.

4. Infrastructure

• Evaluate and integrate emerging AI technologies, including agent frameworks, LLM providers, vector databases, and inference tooling.
• Make pragmatic decisions about what belongs in the core platform versus experimentation.
• Help shape Axium's long-term technical direction in agentic AI infrastructure.

5. Scalability, Reliability & Cost

• Design systems that scale from thousands to millions of supply chain events.
• Address challenges related to performance, fault tolerance, observability, and cost optimisation.
• Ensure SupplyOS meets enterprise expectations for uptime, security, and operational resilience.