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Radiant is an AI infrastructure provider serving enterprises and other organizations running large-scale AI workloads. Its FlightDeck platform provides observability and operational management, while its infrastructure portfolio includes bare-metal and virtual-machine compute, GPUs, managed Kubernetes, Slurm, storage, networks, and datacenter capacity. Radiant also develops sovereign and hyperscaler solutions for teams that need secure, operated, and scalable AI environments. The company’s hiring spans the infrastructure, artificial intelligence, and enterprise technology domains.
Principal Backend Software Engineer, AI Infrastructure
Lead backend architecture for Radiant’s GPU orchestration, inference-serving systems, and AI Cloud APIs. Set technical standards and mentor engineers across squads.
Description
- Build core services for Radiant AI Cloud.
- Design Go backend services for AI infrastructure, networking, inference orchestration, and model lifecycle management.
- Lead engineering design, architecture reviews, and plans for evolving systems.
- Work with platform and infrastructure teams to deliver reliable, secure production services.
- Set technical standards and improve code quality, observability, and maintainability across teams.
- Find and address architectural bottlenecks, performance problems, and scaling challenges.
- Coordinate strategy and technical leadership with principal engineers.
- Work with infrastructure and machine learning colleagues to deliver high-performance AI systems.
- Mentor engineers across multiple squads without direct reports.
- Guide engineering direction, design decisions, and collaboration across teams.
Requirements
- Demonstrated expertise in Go and cloud-native backend development.
- Extensive experience designing and deploying production distributed systems and APIs, including gRPC and REST.
- Strong understanding of Kubernetes internals, including primitives, deployments, and reconciliation loops.
- Experience with PostgreSQL or a comparable high-performance data store.
- Experience with CI/CD, observability, security, and automation practices.
- Ability to provide technical leadership, mentor colleagues, shape architecture, and influence across teams.
- Experience with AI/ML infrastructure tools such as vLLM, KServe, Ray, or Triton is preferred.
- Familiarity with Python, particularly ML libraries and model interfaces, is preferred.
- Familiarity with GPU scheduling, inference pipelines, or orchestration of resource-constrained workloads is preferred.
- Exposure to GPU orchestration frameworks or services for model training or inference.
- Understanding of multi-tenant systems, isolation approaches, and secure infrastructure for AI workloads.
- Authorized to work in the role’s country without sponsorship.
Benefits
- 25 days of annual leave.
- Private medical insurance through Bupa.
- Cycle to Work Scheme.
- Gympass membership, with access to gyms and wellbeing apps.
- Participation in the company share programme.
- Enhanced parental pay and leave.
- Dedicated time to learn skills, work on projects, or explore interests.
- Open communication, regular feedback, and a culture focused on results over hierarchy, process, and ego.
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