Mid-level Software Engineer (Generative AI Cloud Infrastructure)

Company: Arc.dev

Location: Location not specified (Remote)

Type: Full-time

Level: mid

Remote: Yes

Posted: 2026-02-25

About this role

*[Open to candidates based in the US / UK OR Western Europe]*

Mid-Level Software Engineer – AI Cloud & LLM Infrastructure

Full-Time · Remote or Hybrid · Founding Team Opportunity

About Us

We are building a Gen AI Acceleration Cloud an end-to-end platform for the full generative AI lifecycle. Our focus is to deliver blazing-fast LLM inference, scalable fine-tuning, and modern AI cloud infrastructure that GPUs, SmartNICs/DPUs, and ultra-fast networking fabrics.

Our platform powers mission-critical workloads with:

● On-demand & managed Kubernetes clusters

● Slurm-based training clusters

● High-performance inference services

● Distributed fine-tuning and eval pipelines

● Global data centers &heterogeneous GPU fleets

We are looking for a jr-mid Software Engineer to design, build, and scale the core systems behind our AI cloud.

What You’ll Work On

AI Cloud Infrastructure

  • Develop and maintain reliable backend services running across cloud data centers.
  • Assist in building automation for GPU management, VM provisioning, and high-throughput storage systems.
  • Contribute to distributed systems and pipelines that support AI workloads.

LLM & GPU Virtualization Platform

  • Help build the software layer for GPU clusters with modern accelerators (H100, GB200, GB300).
  • Work on GPU virtualization and management (PCIe passthrough, MIG, SR-IOV) under guidance.
  • Support scaling and optimization of storage and data systems for AI training datasets.

Observability, Reliability & Automation

  • Contribute to monitoring and observability stacks (Prometheus, Grafana, OpenTelemetry).
  • Help implement automated node lifecycle management for distributed training and inference.
  • Assist in building testing frameworks for resiliency and fault tolerance.

Core Platform Engineering

  • Contribute to internal and open-source platform components.
  • Build developer tooling, SDKs, and documentation for platform services.
  • Support research and implementati...

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