Senior Cloud Platform Engineer

Job description

About the employer the employer is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence. We’re a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact. If you’re passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises. About the role We are seeking a Senior Cloud Platform Engineer to design, build, and evolve scalable, secure, and cost-efficient cloud platforms on GCP. You will build reusable platform blueprints, infrastructure abstractions, and automated workflows that simplify infrastructure provisioning and application delivery. The role requires deep technical expertise, strong troubleshooting skills, and an ownership mindset to drive initiatives from design through production. What you'll do Platform Engineering & Infrastructure • Design and operate reliable cloud-native platforms on GCP, with GKE at their core. • Build reusable platform blueprints, infrastructure modules, and abstractions to enable standardized, self-service infrastructure provisioning. • Manage Kubernetes cluster lifecycle, upgrades, scaling, performance, and resource utilization. • Apply infrastructure-as-code and platform engineering practices to improve reliability, security, and cost efficiency. GitOps & Automation • Build and maintain GitHub Actions/Workflows and GitOps deployment pipelines using Argo CD or Flux. • Implement policy-driven deployments and automated guardrails using OPA/Gatekeeper and Kyverno. • Develop automation and internal tooling using Python, Bash, or Go to eliminate manual operations and improve developer experience. Networking & Troubleshooting • Design and troubleshoot Kubernetes networking, ingress, service discovery, and traffic management. • Work with gateways and service mesh technologies such as Istio, NGINX, and HAProxy. • Diagnose complex production issues across cloud infrastructure, Kubernetes, and deployment workflows. Engineering Ownership • Collaborate with engineering teams to simplify application onboarding and improve platform adoption. • Drive initiatives end to end, from design and implementation to production readiness and operational support. • Apply security best practices across IAM, workload identity, network policies, and platform governance. • Identify cost optimization opportunities through capacity planning, autoscaling, workload rightsizing, and resource utilization improvements. Benefits • You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space • You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best • The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best • You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI • We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves

Requirements

• 6+ years of experience in cloud, platform, or infrastructure engineering.
• Deep hands-on expertise in GCP and Kubernetes, including production experience with GKE.
• Strong experience with infrastructure as code (IaC), using tools such as Terraform, Pulumi, Crossplane, or equivalent.
• Experience with GitOps (Argo CD/Flux) and GitHub Actions/Workflows.
• Familiarity with policy-as-code tools such as OPA/Gatekeeper or Kyverno.
• Proficiency in Python, Bash, or Go for automation and tooling.
• Strong understanding of cloud networking, gateways, Linux, and distributed systems.
• Proven troubleshooting skills and the ability to independently own and deliver complex technical initiatives.
• Experience building reusable infrastructure modules, platform blueprints, or developer self-service capabilities.
• Experience with MLOps, AI infrastructure, GPU workloads, and Kubernetes-based AI platforms.
• Exposure to OCI or AWS in multi-cloud environments.
• Familiarity with observability tools such as Prometheus, Grafana, Loki, or the employer

Skills