Senior Software Engineer (Generative AI Cloud Infrastructure)

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

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 Senior Software Engineer to design, build, and scale the core systems behind our AI cloud.

What You’ll Work On

High-Performance AI Cloud Infrastructure

● Design and maintain fault-tolerant, high-availability backend services running across global data centers.

● Build operators and automation systems for:

○ GPU management

○ Infiniband partitioning

○ VM provisioning

○ High-throughput storage provisioning

LLM & GPU Virtualization Platform

● Build the IaaS software layer for new GPU clusters with thousands of next-gen accelerators (H100, GB200, GB300).

● Work on scalable GPU virtualization (PCIe passthrough, MIG, SR-IOV, VFIO). Massive-Scale Storage & Data Systems

● Contribute to a global multi-exabyte, high-performance object store optimized for pretraining datasets.

Build distributed data loaders, caching layers, metadata services, and throughput-optimized pipelines.

Observability, Reliability &Automation

● Develop advanced observability stacks (Prometheus, Grafana, OpenTelemetry).cDesign automated node lifecycle management for large-scale distributed training and inference.

● Build robust testing frameworks for resiliency, failover, and fault tolerance. Core Platform Engineering

● Contribute to the core internal + open-source platform components.

● Write tooling, SDKs, and documentation for developer-facing services.

● Research decentralized AI workloads and build reference architectures.

Requirements

Fundamentals

● 5+ years of production software engineering experience.

● Strong proficiency in one or more backend languages (Golang highly preferred; Rust/Python also valued).

● 5+ years building high-performance, well-tested, production-grade distributed services.

Cloud & Systems Experience

● Experience with distributed microservices across AWS/GCP/Azure.

● Deep understanding of systems fundamentals:

○ Concurrency

○ Memory management

○ High-performance I/O

○ Distributed consensus

○ Large-scale system design

Kubernetes / Infrastructure Expertise (Big Plus)

● Kubernetes internals: custom operators, CRDs, schedulers, or networking/storage plugins.

● Experience with Cluster API, KubeVirt, or similar orchestration tooling. Virtualization / Compute (Big Plus)

● Experience with hypervisors (QEMU/KVM, cloud-hypervisor).

● PCIe passthrough, SR-IOV, GPU virtualization, MIG, NVLink topologies.

● Experience with DPUs/SmartNICs.

Networking (Big Plus)

● Infiniband / RDMA

● VLAN/VXLAN/VPC

● OVS/OVN

● High-performance DC networking

High-Performance Compute (Plus)

● CUDA, NCCL, GPU drivers, parallel training stacks

● Experience with GPU scheduling, workloads, and distributed ML

Infrastructure Automation &Tooling (Expected)

● Terraform, Ansible, CI/CD

● GitHub Actions, ArgoCD

● Prometheus, Grafana, ELK, OpenTelemetry

Preferred Experience

● Built or operated IaaS/PaaS systems

● Experience with large-scale storage systems (Ceph, Lustre, or custom object stores)

● Knowledge of vLLM, TensorRT-LLM, TGI, or other LLM-serving frameworks

● Experience building infra for ML, training, inference, or fine-tuning

Responsibilities

● Perform architecture &research for distributed and decentralized AI workloads.

● Build and maintain foundational infrastructure powering training, inference, and fine-tuning.

● Contribute to core, open-source platform components.

● Own end-to-end services from design → implementation → operations.

● Create testing frameworks for robustness, failover, and performance.

● Collaborate across hardware, product, and ML teams to design next-gen infra.

Who You Are

● A deeply technical engineer who thrives in complex systems work.

● Strong communicator who writes clear design docs.

● Curious, low-ego, and great at collaborating with cross-functional teams.

● Motivated by building world-class AI infrastructure from the ground up.

● Thrives in zero-to-one, fast-moving startup environments.

Compensation

● Competitive salary

● Meaningful early equity

● Benefits

● Salary determined by experience and location.