MoznSenior Cloud Platform Engineer
Mozn is hiring a Senior Cloud Platform Engineer in Riyadh, Dubai and Bengaluru. Level rates it ; you can apply on Mozn.
Level's read on this job
- Little AI ●○○○ is how Level rates this role: aI is not part of the work.
- The posting mentions Runway, Google Cloud and Kubernetes among its tools and skills.
- Level classes it as a senior role.
- Mozn has 17 other open roles on Level.
- Posted within the past week.
AI in this role
Build and scale cloud platforms and infrastructure on GCP to support enterprise AI solutions.
About Mozn
MOZN 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.
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.
Preferred Qualifications
- 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 Datadog.
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
How we rate this
Senior Cloud Platform Engineer at Mozn rates 30 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Tell me about a project where platform engineering was part of your work. What did you do?
- Tell me about a project where devops was part of your work. What did you do?
- Tell me about a project where cloud architecture was part of your work. What did you do?
- Tell me about a project where gitops was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: ML Ops, Platform Engineering, DevOps, Cloud Architecture, and Gitops. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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