DevOps Platform Engineer

About the role

AppsFlyer is looking for an experienced DevOps Platform Engineer to join its Application Infrastructure team. You will design, build and operate scalable platforms and infrastructure that let engineering teams develop, deploy and run services efficiently, securely and reliably, in a large-scale production environment using AWS, Kubernetes, Infrastructure as Code, automation, observability and AI-driven technologies.

Key responsibilities

• Design, build and maintain application infrastructure and platforms used by engineering teams
• Develop scalable, reliable and secure infrastructure on AWS
• Build and improve CI/CD pipelines, deployment processes and infrastructure automation
• Manage and operate Kubernetes-based production environments
• Develop self-service tools and platform capabilities that improve developer productivity
• Improve system reliability, availability, performance and scalability
• Define and implement best practices for infrastructure, deployments, observability and security
• Lead troubleshooting, incident investigation and root cause analysis
• Evaluate and implement AI-based tools, including AI agents, LLM-based tools and AIOps capabilities

Required profile

• 3-5 years of hands-on experience in DevOps, Platform Engineering or Infrastructure Engineering
• Strong hands-on experience with AWS in production environments
• Experience with AWS services such as EKS, EC2, IAM, VPC, Route 53, S3, RDS, Lambda, CloudWatch or similar
• Experience writing automation or production-grade code in Python, Go, Bash or a similar language
• Strong troubleshooting skills and ability to work independently and take ownership
• Strong English communication skills and ability to collaborate across teams

Required skills

• Kubernetes and containerized environments
• Infrastructure as Code, preferably Terraform
• CI/CD pipelines with GitHub Actions, GitLab CI, Argo CD or similar
• Linux, networking, DNS, load balancing and distributed systems
• Monitoring, logging, tracing and observability platforms
• AI experience: LLM APIs, AI coding assistants, prompt engineering, and knowledge of CAG, RAG, MCP or AIOps is an advantage

Bonus points: data platforms, multi-region/multi-account AWS, GitOps tools, service mesh, Datadog/Prometheus/Grafana/OpenTelemetry, cloud security and Vault.