Cloud Deployment Engineer (ai Security)

F5 F5 · Enterprise · Dublin, Ireland

Customer-facing Cloud Deployment Engineer focused on deploying and optimizing AI Security solutions, including LLM deployment patterns and real-time AI applications, across public cloud environments (AWS, Azure). The role involves advising clients on infrastructure, scaling, and fine-tuning for low-latency performance and cost-efficiency, with a focus on RAG, fine-tuning, and GPU/CPU optimization.

What you'd actually do

  1. Own end-to-end deployment activities, from planning and configuration to implementation, ensuring project-based delivery across AWS and Azure environments.
  2. Provide expert advisory services to clients, including best practices for infrastructure optimization, scaling, and fine-tuning post-deployment.
  3. Advise customers on the deployment of AI Security and security orchestration, ensuring low-latency performance for real-time AI applications.
  4. Conduct post-deployment 'Health Checks' to analyze GPU utilization, recommending instance rightsizing (e.g., A100 vs. H100) to balance inference speed with TCO (Total Cost of Ownership)
  5. Continuously evaluate deployment processes to improve efficiency, identify gaps, and enhance operational performance for our AI Security products.

Skills

Required

  • 3+ years working with public cloud platforms (AWS, Azure)
  • Cloud infrastructure setup, deployment, and optimization
  • Experience with LLM deployment patterns (RAG, fine-tuning)
  • Understanding of security risks unique to generative AI
  • Experience with GPU/CPU sizing tradeoffs for performance and cost balance
  • Creating and managing technical documentation (deployment playbooks, operational guides)
  • Scripting tools and languages (e.g., Python, Bash)
  • Managing customer relationships
  • Interpersonal and communication skills
  • Engaging stakeholders and delivering tailored deployment solutions
  • Managing deployment projects (scoping, resource allocation, delivering on timelines)
  • Problem-solving skills
  • Monitoring and orchestration tools (Kubernetes, Terraform, Prometheus or similar)
  • Core cloud and web technologies (APIs, HTTP, DNS)
  • Linux environments
  • Networking fundamentals

Nice to have

  • F5 products
  • Red Hat Certified Specialist in OpenShift Administration
  • Post-deployment infrastructure fine-tuning or optimization techniques

What the JD emphasized

  • AI Security
  • security orchestration
  • low-latency performance
  • real-time AI applications
  • LLM deployment patterns
  • RAG
  • fine-tuning
  • GPU/CPU sizing tradeoffs

Other signals

  • customer-facing role
  • delivering impactful cloud deployment solutions
  • design, implement, and optimize cloud-based projects
  • AI Security and security orchestration
  • low-latency performance for real-time AI applications
  • LLM deployment patterns (RAG, fine-tuning)
  • GPU/CPU sizing tradeoffs