DontApply.Club
Login Register

Forward Deployed Engineer

Insearchmgt — Taiwan · Posted ~3 hours ago

Senior

Skills

Python Golang Kubernetes Docker Cloud-native systems Enterprise system deployment Root-cause analysis AI workflow development Cloud Native Multimodal AI

🔓 Log in to save this job, tailor your resume & track your apply process — 7 days free, no card needed.

Log in to add to target list

Summary ✨ AI‑Generated

A customer-facing engineering role for an experienced software engineer who enjoys solving ambiguous problems and rapidly moving from prototype to production. You will build multimodal AI workflows, deploy them across Kubernetes, Docker, and cloud-native environments, integrate enterprise systems, and improve reliability based on customer feedback.

Highlights

Work directly with technical leadership, customers, and engineering teams to turn ambiguous problems into deployed solutions. The role combines multimodal AI, cloud-native infrastructure, rapid prototyping, enterprise deployment, and real-world customer feedback.

Description

Summary Our client is a software product company, with a strong focus on product excellence and customer success, the company continues to invest in AI, Cloud Native, and data platform technologies to deliver high-quality, scalable enterprise solutions. Responsibilities Collaborate closely with CTO, CPO, clients, internal stakeholders to define problems and scope solutions. Build and deploy multimodal AI workflows using modern frameworks. Integrate and scale solutions in Kubernetes, Docker, and cloud-native environments. Iterate quickly — from prototype to deployment — based on real customer feedback. Work with product and engineering team to improve model performance and system reliability. Support on-site or remote deployments when needed. Requirements 5+ years of software product engineering experience; proficient in Python or Golang, with strong ability to efficiently find root causes under unclear information/requirements Hands-on experience with enterprise system deployment, containerization, CI/CD, and monitoring tools Experience independently owning product technical architecture, AI model integration projects, or large-scale project delivery Solid knowledge of Linux, networking, API integration, databases (SQL/NoSQL), and at least one major cloud platform (AWS / Azure / GCP) Willingness to travel or provide on-site support based on project needs Proactive & self-driven, perspective-taking, collaborative and High sense of ownership