KoiReader Technologies is seeking a skilled Lead Infrastructure Engineer to own the architecture of our cutting-edge Bare Metal and Edge Computing platform. You will play a pivotal role in orchestrating our AI/GenAI solutions directly on on-premise edge servers, ensuring high availability and seamless delivery for Fortune 500 clients in environments where the public cloud is often not an option.
Roles & Responsibilities
Edge Infrastructure Management: Design, deploy, and maintain lightweight Kubernetes infrastructure (RKE2, K3s) directly on bare-metal servers, ensuring robustness in constrained environments.
GitOps & Automation: Architect and maintain robust CI/CD pipelines using GitLab, adhering to GitOps principles to automate application delivery to distributed edge nodes.
Release Engineering: Package, configure, and automate complex AI product releases using Helm charts across Development, Test, and Production environments.
Observability: Integrate and manage the full Grafana Observability Stack (Prometheus, Loki, Grafana, Tempo, and Promtail) for deep monitoring of hardware health, application performance, and cluster logs.
System Optimization: Monitor node and kernel-level metrics to drive cost optimization, performance tuning, and capacity planning for high-compute AI workloads.
Client Collaboration: Lead technical discussions with client IT teams to facilitate secure deployment and support of our products within their on-premise data centers.
Skills Required
Edge Orchestration: Deep expertise in Kubernetes, specifically with RKE2 or K3s setup from scratch. You must understand how to build a cluster without managed cloud services.
Bare Metal Mastery: Hands-on experience configuring and managing physical servers (Linux/Ubuntu/RHEL). You should be comfortable with PXE booting, file systems, and Linux kernel tuning.
Physical Networking: Strong understanding of Layer 2/Layer 3 networking (BGP, ARP), Load Balancing on bare metal (MetalLB, Kube-VIP), and firewalls.
Scripting & Automation: Proficiency in Bash and Python for automating system administration tasks and hardware provisioning.
Monitoring: Expert-level knowledge of the Grafana/Prometheus ecosystem, specifically for monitoring physical resources.
Communication: Excellent communication skills paired with a relentless drive to master emerging edge architectures.
Brownie Points (Nice to Have)
Hardware Acceleration: Experience managing NVIDIA GPUs, configuring CUDA drivers, and using the NVIDIA Container Toolkit.
Security: Knowledge of System Security (SAST/DAST), Air-Gapped deployments, and OS hardening (CIS Benchmarks).
Storage: Experience with distributed block storage for edge (e.g., Longhorn, Rook/Ceph, or Local Path Provisioning).
What We Offer
Culture: A meritocracy-driven, candid startup culture that values autonomy.
Tech: Work with the latest GenAI and Computer Vision technologies as an NVIDIA partner.
Impact: Architect high-availability infrastructure that orchestrates GenAI and Computer Vision workloads from the Edge to the Cloud, powering major global supply chains.