Qube Research & Technologies
quantitative and systematic investment manager
AIPlatformEngineer
“AI Platform Engineer at Qube Research & Technologies. Skills: Kubernetes, AWS, Python, Terraform. Design, deploy and maintain infrastructure supporting AI and LLM workloads. Manage Kubernetes operations”
What You'll Achieve.
deliver high-quality returns for our investors; supporting performance, reliability and operational efficiency; meet platform performance requirements
Industry & Context.
What They're Looking For.
Must Have
4 or more years of experience in Cloud Engineering, DevOps or Platform Engineering, Kubernetes experience including cluster operations, workload scheduling and multi tenant environments, AWS experience including networking, IAM, EKS, EC2 and infrastructure cost management, Proficiency in Python, infrastructure as code tooling such as Terraform, Experience building and operating continuous integration and deployment pipelines, Experience defining and operating against infrastructure service objectives and operational metrics, ownership mindset with the ability to operate effectively in fast paced environments
Nice to Have
Familiarity with large language model serving infrastructure or GPU enabled workloads, Experience with vector databases, retrieval systems or internal platform APIs, Exposure to performance sensitive or low latency infrastructure environments, AWS or Kubernetes certifications
What You'll Do.
deploy and maintain infrastructure supporting AI and LLM workloads
Manage Kubernetes operations
Develop deployment strategies
Manage AWS infrastructure
Build reusable infrastructure as code
Develop automated deployment workflows
Build monitoring and observability tooling
Implement authentication
Support internal engineering users
Collaborate with engineering and research stakeholders
How You'll Work.
Team & Collaboration
Collaborate with engineering and research stakeholders; Work with product team
Applying for this AI Platform Engineer role?
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