DevOps Platform Engineer

Posted 4 Days Ago
Be an Early Applicant
Herzliya, ISR
In-Office
Mid level
AdTech • Marketing Tech
The Role
Design, build, and operate scalable AWS and Kubernetes platforms, infrastructure automation, CI/CD pipelines, and developer self-service tools. Improve reliability, security, observability, and production performance while leading troubleshooting and incident investigations. Integrate AI agents, LLM tools, and AIOps into infrastructure workflows. Collaborate across engineering, security, architecture, data, and cloud teams, and support complex multi-region or multi-account environments.
Summary Generated by Built In

We are looking for an experienced DevOps Platform Engineer to join our Application Infrastructure team.

In 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.

You will work in a complex, large-scale production environment using AWS, Kubernetes, Infrastructure as Code, automation, observability, and AI-driven technologies.

What you’ll do:

  • 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 and experience.
  • 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 for complex production issues.
  • Collaborate with R&D, Security, Architecture, Data, and Cloud teams.
  • Evaluate and implement AI-based tools for infrastructure automation, operational efficiency, incident analysis, and developer workflows.
  • Develop or integrate AI agents, LLM-based tools, and AIOps capabilities into platform engineering processes.

What you have:

  • 3-5 years of hands-on experience in DevOps, Platform Engineering, or Infrastructure Engineering roles.
  • Strong hands-on experience working with AWS in production environments.
  • Proven experience with AWS services such as EKS, EC2, IAM, VPC, Route 53, S3, RDS, Lambda, CloudWatch, or similar services.
  • Strong experience with Kubernetes and containerized environments.
  • Hands-on experience with Infrastructure as Code tools, preferably Terraform.
  • Experience building and maintaining CI/CD pipelines using GitHub Actions, GitLab CI, Argo CD, or similar technologies.
  • Experience writing automation or production-grade code using Python, Go, Bash, or a similar language.
  • Strong understanding of Linux, networking, DNS, load balancing, and distributed systems.
  • Experience with monitoring, logging, tracing, and observability platforms.
  • Strong troubleshooting skills and the ability to investigate complex production issues.
  • Ability to work independently, take ownership, and drive projects from design through production.
  • Strong English communication skills and the ability to collaborate across multiple engineering teams.

AI Experience you have: 

  • Hands-on experience using AI and Generative AI tools as part of software development, infrastructure, or operational workflows.
  • Experience working with LLM APIs, AI coding assistants, or AI automation tools.
  • Ability to identify processes that can be improved through AI and translate them into practical engineering solutions.
  • Understanding of prompt engineering, responsible AI usage, and the secure handling of sensitive information.
  • Experience with CAG, AI agents, RAG, MCP, LLM integrations, or AIOps solutions is an advantage.

Bonus points:

  • Experience working with data platforms, data infrastructure, or large-scale data processing systems.
  • Understanding of data pipelines, data ingestion, streaming systems, or distributed data architectures.
  • Experience operating large-scale, multi-region, or multi-account AWS environments.
  • Experience with GitOps tools such as Argo CD or Akuity.
  • Experience with service mesh, API gateways, or service discovery solutions.
  • Experience with Datadog, Prometheus, Grafana, OpenTelemetry, or similar observability tools.
  • Experience with cloud security, secrets management, and Vault

As 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.

“As a Customer Obsessed company, we must first be Employee Obsessed. We need to make sure that we provide the team with the tools and resources they need to go All-In.” Oren Kaniel, CEO

Skills Required

  • 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 including EKS, EC2, IAM, VPC, Route 53, S3, RDS, Lambda, and CloudWatch
  • Strong experience with Kubernetes and containerized environments
  • Hands-on experience with Infrastructure as Code tools, preferably Terraform
  • Experience building and maintaining CI/CD pipelines using GitHub Actions, GitLab CI, Argo CD, or similar technologies
  • Experience writing production-grade automation code using Python, Go, Bash, or a similar language
  • Strong understanding of Linux, networking, DNS, load balancing, and distributed systems
  • Experience with monitoring, logging, tracing, and observability platforms
  • Strong troubleshooting skills and ability to investigate complex production issues
  • Ability to work independently, take ownership, and drive projects from design through production
  • Strong English communication and cross-functional collaboration skills
  • Hands-on experience using AI and generative AI tools in software development, infrastructure, or operational workflows
  • Experience with LLM APIs, AI coding assistants, or AI automation tools
  • Understanding of prompt engineering, responsible AI usage, and secure handling of sensitive information
  • Experience with CAG, AI agents, RAG, MCP, LLM integrations, or AIOps solutions
  • Experience with data platforms, data infrastructure, or large-scale data processing systems
  • Understanding of data pipelines, data ingestion, streaming systems, or distributed data architectures
  • Experience operating large-scale, multi-region, or multi-account AWS environments
  • Experience with GitOps tools such as Argo CD or Akuity
  • Experience with service mesh, API gateways, or service discovery solutions
  • Experience with Datadog, Prometheus, Grafana, OpenTelemetry, or similar observability tools
  • Experience with cloud security, secrets management, and Vault

AppsFlyer Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AppsFlyer and has not been reviewed or approved by AppsFlyer.

  • Wellbeing & Lifestyle Benefits — Wellbeing support is positioned as a meaningful part of the rewards package, including private health insurance and wellness offerings like fitness classes. Additional extras such as events, work‑from‑home support, and global mobility opportunities are portrayed as adding tangible value beyond cash compensation.
  • Equity Value & Accessibility — Equity is framed as broadly accessible, with stock options described as available to all employees. This expands the total rewards mix and can make overall compensation feel stronger even when salary alone is debated.
  • Strong & Reliable Incentives — Total compensation in certain technical and revenue roles is presented as capable of reaching competitive levels, implying meaningful upside where role/market fit is strong. Sales compensation is described as potentially attractive on-target, which can reinforce perceived earning opportunity when performance aligns with plan design.

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The Company
HQ: San Francisco, CA
1,625 Employees
Year Founded: 2011

What We Do

AppsFlyer helps brands make good choices for their business and their customers through innovative, privacy-preserving measurement, analytics, fraud protection, and engagement technologies. Built on the idea that brands can increase customer privacy while providing exceptional experiences, AppsFlyer empowers thousands of creators and 8,000+ technology partners to create better, more meaningful customer relationships. To learn more, visit www.appsflyer.com.

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