Job Description

Most platform engineers maintain what already exists. This role is about deciding what should exist. As Staff Platform Engineer at Axium Industries, you will be one of the principal architects of SupplyOS — our agentic AI platform powering procurement, inventory, manufacturing, and logistics for large enterprises across Asia. You will define the long-term technical direction, build the primitives every team depends on, and solve the hardest architectural problems as we grow from early deployments to regional scale. If you want to build the foundational layer that makes advanced AI work in complex, real-world enterprise environments — this is that job.

API : Server & workflow engine ownership
0→1: Platform primitives built from scratch
SE Asia : Enterprise rollouts at regional scale
This is a principal-level, high-trust role.
You won't be handed a ticket queue. You'll set the engineering north star — owning standards for reliability, observability, performance, and developer experience across the entire platform. Ideal for someone who has built platforms others depend on and now wants to do it at a company where the problem space is genuinely unsolved.

WHAT YOU'LL OWN

🏗️ Architect the core of SupplyOS

Design and build the major systems that power everything else — our API server, workflow engine, multi-agent orchestration layer, RAG infrastructure, and intelligent memory systems. These are the primitives every other team builds on top of.

⚡ Make FDEs radically faster

Spot recurring patterns across customer deployments and turn them into platform abstractions. Your best work here won't be code — it'll be the code you make unnecessary for everyone else to write.

🔭 Evaluate and integrate emerging AI tech

Stay ahead of the agent frameworks, LLM providers, and vector databases shaping the space. Decide what belongs in our stack with principled, production-tested judgment — not hype.

📈 Scale from thousands to millions of events

Solve real constraints around reliability, performance, and cost as supply chain event volume grows by orders of magnitude. The hard problems here are distributed systems problems — consistency, failure modes, and latency at scale.

🤝 Bridge platform and field reality

Partner with Forward Deployed Engineers and product teams to translate what's happening in real customer environments into platform capabilities. The best abstractions come from knowing what's actually hard in production.

Job Requirements

Requirements:

• Deep distributed systems expertise: You've architected backend systems that handle real scale and complexity and you understand consensus protocols, eventual consistency, and the subtle tradeoffs that separate systems that work from systems that work reliably and deliver enterprise workloads.
• Production polyglot: You ship production-grade software in Go, Python, and JavaScript/TypeScript. You have gone beyond "can write code" to "writes code that survives production at 3am".
• Cloud infrastructure depth: You're fluent in building production cloud systems with Terraform and Docker. Infrastructure-as-code isn't just a buzzword, it's how you think about deploying and scaling systems.
• Platform builder credentials: You have a proven track record of building platforms that multiple teams actually use and depend on and you've felt the pain of bad abstractions and know what makes developers productive.
• Data engineering competence: You understand how to move, transform, and validate data at scale. ETL isn't a mystery, it's a solved problem you've implemented many times. Bonus points if you've wrestled with Databricks in production.

Skills