Senior Engineer, AI & Data Platform
Summary
Hands-on senior engineer who builds and operates POET's manufacturing data and AI platform in Singapore: data pipelines and equipment integrations, factory/cloud infrastructure (Linux, Docker, GPUs, CI/CD), Python backend services, and LLM/agentic workflows to improve testing, yield, and cost.
We are seeking a Senior AI & Data Platform Engineer to build and operate the technical foundation for our Data & AI Transformation initiatives, owning the manufacturing data platform, infrastructure, equipment data integration, AI infrastructure, MLOps, and agentic systems that improve testing, yield, and cost. This hands‑on, end‑to‑end role works closely with engineering, manufacturing, and planning teams to turn real‑world challenges into reliable, production‑ready software and AI solutions, from architecture and development through deployment, monitoring, and continuous improvement, while ensuring critical manufacturing decisions remain deterministic, auditable, and scalable.
Job Responsibilities
- Build and operate AI/ML infrastructure, including data pipelines, model training, LLM serving, retrieval systems, agent runtimes, evaluation, and monitoring.
- Own production infrastructure across factory and cloud environments, including Linux, Docker, GPUs, CI/CD, networking, and infrastructure-as-code.
- Develop scalable manufacturing data platforms and ingestion pipelines integrating tester, equipment, vendor, and reporting data.
- Build backend services, APIs, applications, and automation using Python and modern web technologies.
- Deploy and operate AI/LLM solutions, including agentic workflows for manufacturing reporting, log analysis, and natural-language data querying.
- Establish robust engineering practices across testing, monitoring, version control, documentation, and continuous deployment.
- Collaborate with vendors and internal teams to integrate systems and translate manufacturing needs into solutions that improve yield, efficiency, cost, and operations.
Requirements
- 4+ years of software engineering experience, with strong Python skills.
- Strong SQL, database, ETL, and data pipeline experience, including PostgreSQL or MySQL.
- Production infrastructure experience with Linux, Docker, CI/CD, and AWS, Azure, or GCP.
- Backend and AI/ML infrastructure experience with technologies such as FastAPI, Flask, Django, vLLM, MLflow, LangGraph, or MCP.
- Hands‑on experience deploying AI/ML and LLM solutions, including agentic workflows, with proven use of AI-assisted development tools such as Claude Code, Codex, or Cursor to deliver production software.