DevOps Engineer

Linkup

About The Position

Linkup is hiring a DevOps Engineer to help build and operate the infrastructure behind its AI-focused web search engine. The role works closely with CTO Denis Charrier, the founders, and the technical team, and has a central part in shaping the company’s engineering and AI-powered products. Linkup describes its work as building a structured, continuously updated knowledge layer that delivers fresh, reliable information to AI agents. The engineer will build and operate large-scale distributed systems, develop infrastructure for indexing, retrieval, and monitoring, and automate deployment, scaling, and observability. The role also focuses on improving performance, scalability, reliability, and resource usage; contributing to architecture and system-design discussions; and collaborating with machine-learning and backend teams on CI/CD and model-deployment workflows. The position offers a flexible remote-work policy; further details are linked in the posting.

Requirements

At least 2 years of strong experience with cloud infrastructure and container orchestration such as Kubernetes; experience with AWS, GCP, or Azure is preferred.
Understanding of distributed systems, networking, and infrastructure as code such as Terraform.
Care about performance, reliability, and system observability.
Enjoy debugging difficult production issues and optimizing infrastructure bottlenecks.
Curiosity about AI infrastructure, data pipelines, and large-scale retrieval systems.
Ability to thrive in a fast-paced, high-ownership startup environment.
Excitement about building search for AI agents and belief in Linkup’s mission.

Nice To Haves

Experience with AWS, GCP, or Azure.
Experience or interest in AI infrastructure, data pipelines, and large-scale retrieval systems.

Responsibilities

Build and operate large-scale distributed systems powering AI-ready web search.
Design, implement, and maintain infrastructure for indexing, retrieval, and monitoring.
Automate deployment, scaling, and observability across environments.
Optimize performance, scalability, and resource usage across the stack.
Participate in architecture discussions and contribute to system design.
Collaborate with machine-learning and backend teams to streamline CI/CD and model-deployment workflows.
Write clean, maintainable infrastructure code and participate in reviews.
Debug production issues and optimize infrastructure bottlenecks.