Principal Software Engineer

What You'll Do As a Principal Software Engineer, you will help set the technical direction for a core part of Radiant's AI cloud, joining one of four teams: Infra & Cluster, Observability, MLOps Training, or MLOps Inference. We'll match you to the team that fits your experience. You'll lead the design and delivery of the distributed systems that run GPU infrastructure and AI workloads at scale, partnering closely with product, infrastructure, SRE, networking, and storage teams, and with customers running the most demanding workloads. This is a hands-on technical leadership role, delivered through architecture, code, and the standards other teams build on. The teams Infra & Cluster: provisioning, lifecycle, and cluster management behind our Bare Metal and Virtual Machine products Observability: FlightDeck, our platform for observing and operating AI infrastructure, and the telemetry behind it MLOps Training: the platform customers use to train models on our GPU clusters, including Managed Kubernetes and Managed Slurm MLOps Inference: the platform customers use to serve models in production   Key Responsibilities Set the technical vision and architecture for your team's area, and lead its design and implementation. Design and build distributed systems that run reliably on GPU infrastructure at scale. Translate product and customer requirements into robust architectures, APIs, and technical designs, working closely with Product. Own the performance, reliability, and cost of your team's systems as the platform grows. Partner with SRE, Infra Ops, and customers on operations, incident response, and the most demanding workloads. Raise the engineering bar across the organisation through mentoring, design and code review, and technical standards.   Your Profile Extensive experience building and operating large-scale distributed systems, infrastructure software, or ML platforms. A track record of technical leadership at staff or principal level, including setting direction across multiple teams and delivering complex, high-stakes systems. Strong hands-on engineering skills in Go, Python, or similar. Deep technical expertise in at least one of: Infra & Cluster: provisioning (PXE, Redfish, IPMI, BMCs, firmware), cluster management, inventory, and lifecycle automation Observability: metrics, logs, traces, OpenTelemetry, streaming pipelines, and high-cardinality time-series data MLOps Training: Kubernetes and Slurm orchestration, PyTorch distributed, NCCL, checkpointing, and fault tolerance MLOps Inference: model serving, batching, autoscaling, GPU utilisation, quantisation, and latency tuning Strong foundations in Kubernetes, containers, Linux, high-performance networking, and GPU clusters. Hands-on experience with technologies such as Redfish, Prometheus, OpenTelemetry, ClickHouse, Kafka, Slurm, vLLM, NVIDIA Triton, or similar. Excellent written and verbal communication, including clear design documents and explaining complex trade-offs to technical and non-technical audiences. Comfortable working directly with customers on highly technical problems.   What You Bring Domain expertise: Bring deep expertise in your team's area, and know where it breaks at scale. Engineering excellence: Write and review code that sets the standard for correctness, performance, and maintainability. Architectural judgement: Make sound long-term decisions on systems that are hard to change once built. Technical leadership: Influence direction across teams without relying on authority, and grow the engineers around you. Systems thinking: Understand how your area interacts with compute, networking, storage, and the rest of the cloud platform. Ownership: Drive capabilities from design through production, operation, and continuous improvement.   Qualities we look for: Set the standard: Every single day, you spot opportunities to constructively shake things up Inspire the change: There's no