Sharon AI, Inc
Senior Infrastructure Engineer
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Senior Infrastructure Engineer (GPUaaS – AI Neocloud)
📍 EMEA | Remote
Sharon AI is building the infrastructure powering the next generation of artificial intelligence. Operating across high-performance GPU compute and AI infrastructure, we’re focused on delivering reliable, scalable and secure solutions that support advanced AI workloads.
As Sharon AI continues to grow, we’re looking for an experienced Senior Infrastructure Engineer to join our team and help build, operate and continuously improve the core infrastructure powering our GPU-as-a-Service (GPUaaS) platform.
Reporting to the Infrastructure Engineering Team Lead, you’ll work across large-scale, multi-tenant infrastructure supporting demanding AI/ML workloads, including large-scale training, fine-tuning and real-time inference. You’ll work closely with platform engineers, ML engineers and product stakeholders to ensure our infrastructure delivers the performance, reliability and efficiency required at scale. This is a hands-on senior technical role suited to an experienced infrastructure, platform or SRE engineer who enjoys solving complex technical challenges and working in fast-paced, AI-native environments.
What You’ll Be Doing
- Build and operate large-scale, multi-tenant infrastructure supporting GPUaaS platforms
- Manage high-performance compute clusters using Kubernetes and/or HPC schedulers such as Slurm
- Build and maintain GPU-optimised infrastructure, including node lifecycle management and cluster scaling
- Develop and maintain Infrastructure-as-Code using Terraform, Ansible or similar tools
- Automate infrastructure provisioning, scaling and configuration
- Improve GPU utilisation, scheduling efficiency and infrastructure cost optimisation
- Build and enhance observability across monitoring, logging and alerting
- Ensure high availability, fault tolerance and disaster recovery capabilities
- Implement and maintain security controls and workload isolation across multi-tenant environments
- Partner with ML and platform teams to optimise infrastructure performance for training and inference workloads
- Provide L3 support for complex platform and infrastructure incidents during standard EMEA working hours
- Participate in incident response, conduct root cause analysis and drive ongoing reliability improvements
- Contribute to capacity planning and broader infrastructure improvements
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What We’re Looking For
- 6–10+ years of experience in infrastructure engineering, platform engineering or SRE roles
- Deep expertise across cloud and/or bare-metal infrastructure environments
- Advanced knowledge of distributed systems and operating infrastructure at scale
- Strong hands-on experience with Kubernetes and container orchestration
- Experience managing or optimising GPU-based systems and workloads
- Strong proficiency with Infrastructure-as-Code tools such as Terraform, Ansible or similar
- Strong programming and scripting skills in Python, Go and/or Bash
- Experience with networking and storage systems in high-performance environments
- Strong observability and performance tuning capabilities
- Proven ability to optimise infrastructure for cost, performance and efficiency
- A security-first mindset, with knowledge of infrastructure hardening practices
- Strong communication, collaboration and technical leadership skills
- Proven experience operating large-scale distributed infrastructure systems
- Hands-on experience with production-grade Kubernetes platforms
- Experience with automation, CI/CD and infrastructure lifecycle management
- A Bachelor’s degree in Computer Science, Engineering or a related field, or equivalent experience
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What Would Be a Plus
- Experience in any of the following areas would be highly regarded:
- GPUaaS, IaaS or neocloud platforms
- AI/ML workloads and frameworks such as PyTorch or TensorFlow
- HPC environments and schedulers including Slurm or Ray
- GPU technologies including CUDA, NCCL or MIG
- Platforms such as Kubeflow, Airflow or similar orchestration tools
- High-performance networking technologies such as RDMA or InfiniBand
- Relevant cloud or Kubernetes certifications
Why Join Sharon AI?
You’ll be joining a rapidly growing technology business working at the forefront of AI infrastructure. This is an opportunity to work on technically complex infrastructure challenges and play a key role in building the platform that supports the next generation of AI workloads.
- Remote-first working environment across EMEA
- Work directly with high-performance GPU infrastructure and AI/ML workloads
- Opportunity to work on large-scale distributed systems and production-grade platforms
- Exposure to GPUaaS, neocloud and next-generation AI infrastructure
- Work closely with platform, ML and product teams
- Opportunity to make a meaningful impact on platform reliability, performance and scalability
If you’re an experienced infrastructure engineer who enjoys working at scale, solving complex technical problems and wants to help build the infrastructure behind the next generation of AI, we’d love to hear from you.
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