{"id":3412644,"url":"https://alion.io/job/appsflyer-devops-platform-engineer","title":"DevOps Platform Engineer","company":{"id":3446,"name":"AppsFlyer","domain":"appsflyer.com","url":"https://alion.io/company/appsflyer","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":81,"open_postings":14,"ghost_share":0,"stale_share":0.571,"repost_share":0,"time_to_fill_p50_days":89,"computed_at":"2026-11-06T05:58:05Z"}},"role":"DevOps","role_family":"DevOps","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Herzliya, Israel"],"countries":["IL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon EC2","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Bash","optional":false},{"name":"CI/CD","optional":false},{"name":"DNS","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"Go","optional":false},{"name":"IAM","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Terraform","optional":false},{"name":"Datadog","optional":true},{"name":"GitOps","optional":true},{"name":"Grafana","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"Prometheus","optional":true},{"name":"Service Mesh","optional":true}],"status":"live","first_seen_at":"2026-08-11T11:39:05Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-11-06T19:46:26Z","board_verified":true,"closed_at":null,"days_open":87,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":87},"description":"We are looking for an experienced DevOps Platform Engineer to join our Application Infrastructure team.\nIn this role, you will design, build, and operate scalable platforms and infrastructure that enable engineering teams to develop, deploy, and run services efficiently, securely, and reliably.\nYou will work in a complex, large-scale production environment using AWS, Kubernetes, Infrastructure as Code, automation, observability, and AI-driven technologies.\nWhat you’ll do:\nDesign, build, and maintain application infrastructure and platforms used by engineering teams.\nDevelop scalable, reliable, and secure infrastructure on AWS.\nBuild and improve CI/CD pipelines, deployment processes, and infrastructure automation.\nManage and operate Kubernetes-based production environments.\nDevelop self-service tools and platform capabilities that improve developer productivity and experience.\nImprove system reliability, availability, performance, and scalability.\nDefine and implement best practices for infrastructure, deployments, observability, and security.\nLead troubleshooting, incident investigation, and root cause analysis for complex production issues.\nCollaborate with R&D, Security, Architecture, Data, and Cloud teams.\nEvaluate and implement AI-based tools for infrastructure automation, operational efficiency, incident analysis, and developer workflows.\nDevelop or integrate AI agents, LLM-based tools, and AIOps capabilities into platform engineering processes.\nWhat you have:\n3-5 years of hands-on experience in DevOps, Platform Engineering, or Infrastructure Engineering roles.\nStrong hands-on experience working with AWS in production environments.\nProven experience with AWS services such as EKS, EC2, IAM, VPC, Route 53, S3, RDS, Lambda, CloudWatch, or similar services.\nStrong experience with Kubernetes and containerized environments.\nHands-on experience with Infrastructure as Code tools, preferably Terraform.\nExperience building and maintaining CI/CD pipelines using GitHub Actions, GitLab CI, Argo CD, or similar technologies.\nExperience writing automation or production-grade code using Python, Go, Bash, or a similar language.\nStrong understanding of Linux, networking, DNS, load balancing, and distributed systems.\nExperience with monitoring, logging, tracing, and observability platforms.\nStrong troubleshooting skills and the ability to investigate complex production issues.\nAbility to work independently, take ownership, and drive projects from design through production.\nStrong English communication skills and the ability to collaborate across multiple engineering teams.\nAI Experience you have: \nHands-on experience using AI and Generative AI tools as part of software development, infrastructure, or operational workflows.\nExperience working with LLM APIs, AI coding assistants, or AI automation tools.\nAbility to identify processes that can be improved through AI and translate them into practical engineering solutions.\nUnderstanding of prompt engineering, responsible AI usage, and the secure handling of sensitive information.\nExperience with CAG, AI agents, RAG, MCP, LLM integrations, or AIOps solutions is an advantage.\nBonus points:\nExperience working with data platforms, data infrastructure, or large-scale data processing systems.\nUnderstanding of data pipelines, data ingestion, streaming systems, or distributed data architectures.\nExperience operating large-scale, multi-region, or multi-account AWS environments.\nExperience with GitOps tools such as Argo CD or Akuity.\nExperience with service mesh, API gateways, or service discovery solutions.\nExperience with Datadog, Prometheus, Grafana, OpenTelemetry, or similar observability tools.\nExperience with cloud security, secrets management, and Vault\nAs a global company operating from 25 offices across 19 countries, we reflect the human mosaic of the diverse and multicultural world in which we live. We ensure equal opportunities for all of our employees and promote the recruitment of diverse talents to our global teams without consideration of race, gender, culture, or sexual orientation. We value and encourage curiosity, diversity, and innovation from all our employees, customers, and partners.\n“As a Customer Obsessed company, we must first be Employee Obsessed. 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