דרושים » תוכנה » Experienced DevOps Engineer (Cortex Cloud)

we are looking for an experienced DevOps Engineer to join our high-performance team. Youll work closely with development teams to design and implement smarter processes and tools, while embracing a GenAI-driven mindset. In this role, you will help build and scale infrastructure that not only keeps our company running smoothly, but also powers next-generation AI-driven applications with speed, resilience, and efficiency.
our companys Technology Stack sample:
AWS, Kubernetes, Terragrunt, Ansible, Jenkins, ArgoCD, Argo-Workflows, Service Mesh, Nginx, CloudFlare, Hashicorp Vault/Consul, Kafka, RabbitMQ, Prometheus, Grafana, VictoriaMetrics, CircleCI
Programming languages: Python, NodeJS, Go, Kotlin
What am I going to do?
Maintain and build a large-scale, highly available cloud infrastructure focusing on K8S.
Improve resiliency and cost efficiency of our cloud infrastructure.
Use GenAI tools to automate troubleshooting, speed up incident resolution, and improve production reliability.
Develop AI-driven self-service solutions to accelerate developer issue resolution and resource provisioning.
Develop and adopt new tools to make Development and Operations processes at our company more efficient.
Collaborate with developers to optimize system performance, reliability, and scale.
Evolve and maintain our companys AWS infrastructure by improving and adopting new services.
Support AI/ML/GenAI services with scalable infrastructure and monitoring.
Maintain our company availability by participating in DevOps on-call shifts.
Mentor DevOps engineers.

we are looking for an experienced DevOps Engineer to join our high-performance team. Youll work closely with development teams to design and implement smarter processes and tools, while embracing a GenAI-driven mindset. In this role, you will help build and scale infrastructure that not only keeps our company running smoothly, but also powers next-generation AI-driven applications with speed, resilience, and efficiency.
our companys Technology Stack sample:
AWS, Kubernetes, Terragrunt, Ansible, Jenkins, ArgoCD, Argo-Workflows, Service Mesh, Nginx, CloudFlare, Hashicorp Vault/Consul, Kafka, RabbitMQ, Prometheus, Grafana, VictoriaMetrics, CircleCI
Programming languages: Python, NodeJS, Go, Kotlin
What am I going to do?
Maintain and build a large-scale, highly available cloud infrastructure focusing on K8S.
Improve resiliency and cost efficiency of our cloud infrastructure.
Use GenAI tools to automate troubleshooting, speed up incident resolution, and improve production reliability.
Develop AI-driven self-service solutions to accelerate developer issue resolution and resource provisioning.
Develop and adopt new tools to make Development and Operations processes at our company more efficient.
Collaborate with developers to optimize system performance, reliability, and scale.
Evolve and maintain our companys AWS infrastructure by improving and adopting new services.
Support AI/ML/GenAI services with scalable infrastructure and monitoring.
Maintain our company availability by participating in DevOps on-call shifts.
Mentor DevOps engineers.

Fiverr is looking for an experienced DevOps Engineer to join our high-performance team. You’ll work closely with development teams to design and implement smarter processes and tools, while embracing a GenAI-driven mindset. In this role, you will help build and scale infrastructure that not only keeps Fiverr running smoothly, but also powers next-generation AI-driven applications with speed, resilience, and efficiency. Fiverr’s Technology Stack sample: AWS, Kubernetes, Terragrunt, Ansible, Jenkins, ArgoCD, Argo-Workflows, Service Mesh, Nginx, CloudFlare, Hashicorp Vault/Consul, Kafka, RabbitMQ, Prometheus, Grafana, VictoriaMetrics, CircleCI Programming languages: Python, NodeJS, Go, Kotlin

What am I going to do?:

* Maintain and build a large-scale, highly available cloud infrastructure focusing on K8S.
* Improve resiliency and cost efficiency of our cloud infrastructure.
* Use GenAI tools to automate troubleshooting, speed up incident resolution, and improve production reliability.
* Develop AI-driven self-service solutions to accelerate developer issue resolution and resource provisioning.
* Develop and adopt new tools to make Development and Operations processes at Fiverr more efficient.
* Collaborate with developers to optimize system performance, reliability, and scale.
* Evolve and maintain Fiverr’s AWS infrastructure by improving and adopting new services.
* Support AI/ML/GenAI services with scalable infrastructure and monitoring.
* Maintain Fiverr availability by participating in DevOps on-call shifts.
* Mentor DevOps engineers.

Equal opportunities:
At Fiverr, we’re not about checklists. If you don’t meet 100% of the requirements for this role but still feel passionate about the position and think you have the right skills and qualifications to excel at it, we want to hear from you. At Fiverr, we prioritize diversity. We celebrate difference and embed it into every aspect of our workplace and product, as well as our community. Fiverr is proud and committed to providing equal opportunity employment to all individuals regardless of race, color, religion, sex, sexual orientation, citizenship, national origin, disability, Veteran status, or any other characteristic protected by law. In addition, Fiverr will provide accommodation to individuals with disabilities or a special need.

Required DevOps Engineer
About the Job:
As a DevOps / Platform Engineer at EdgeHawk Security, you will be responsible for building and operating the cloud and container platforms that power our security systems. You will work primarily with AWS, Kubernetes, Docker, and GitHub Actions, ensuring our infrastructure can reliably handle high-throughput, security-critical workloads. This role focuses on automation, scalability, and operational excellence in production environments exposed to real-world attack traffic.
What will you do?
Own AWS Infrastructure:
Design, deploy, and operate production infrastructure on AWS, including compute, networking, storage, and IAM, with a strong focus on reliability and security.
Build Kubernetes Platforms:
Operate and scale Kubernetes clusters running containerized backend services, including workload isolation, networking, upgrades, and capacity planning.
Containerize Everything:
Create and maintain Dockerfiles for backend services, focusing on small images, secure build practices, and fast startup times.
Automate CI/CD with GitHub:
Design and maintain GitHub Actions pipelines for build, test, container image creation, and deployment to Kubernetes.
Enable Safe Deployments:
Implement deployment strategies such as rolling updates, blue-green, or canary deployments to minimize risk in production.
Infrastructure as Code:
Define and manage AWS and Kubernetes infrastructure using Infrastructure-as-Code practices (Terraform preferred).
Operate & Debug Production Systems:
Monitor, troubleshoot, and debug live systems running in AWS and Kubernetes, participating in incident response and root-cause analysis.
Observability & Reliability:
Build monitoring and alerting using Prometheus/Grafana and logging pipelines to ensure fast detection and resolution of issues.

The Core Platform Engineering group is looking for a passionate, talented, and strong DevOps Engineer to drive the design and development of our next-generation SaaS Management Platform and infrastructure that delivers our Liquid Software vision to thousands of organizations across all major cloud providers (AWS, GCP, & Azure).
You will work with a team of highly-skilled, passionate DevOps engineers building a cloud-native infrastructure to smoothly run our systems and automate all aspects of our engineering platform. You should be driven by technology and enjoy automation, while being passionate about customer satisfaction.
As a DevOps Engineer , you will...
Work with cutting-edge technologies, utilizing the latest tools like Kubernetes, Helm, Prometheus, Thanos, and OpenTelemetry to build next-generation SaaS platforms
Operate across major cloud providers, including AWS, GCP, and Azure to build and scale our infrastructure, while proactively identifying bottlenecks and inefficiencies to implement automation and optimization solutions
Design, deploy, and optimize Kubernetes-based environments for applications to ensure high-availability and scalability
Establish and manage comprehensive monitoring and logging systems, such as Coralogix and Grafana, to proactively identify issues and ensure full uptime in production environments
Collaborate closely with various teams across , including R&D, Product, and Security, to ensure that DevOps practices adhere to security standards and compliance requirements
Participate in technical discussions to influence the roadmap and help make key decisions regarding the successful implementation of cloud platform initiatives
Design innovative solutions for monitoring large-scale SaaS environments, keeping both application and infrastructure challenges in mind
Implement CI/CD automated processes with a heavy emphasis on monitoring tools and deployment orchestration to streamline delivery

As a Site Reliability Engineer on the SASE Platform team, you will play a critical role in building and operating highly available, secure, and globally distributed services. Your mission is to ensure our cloud-native security and networking platform is reliable, scalable, and performant from day one, protecting the users, applications, and data for the world's largest enterprises as they adopt cloud, remote work, and AI
Your Impact:
Proactively collaborate with development teams to embed reliability, scalability, and operability into services from the earliest design stages.
Design, review, and evolve cloud-native architectures to improve availability, performance, cost efficiency, and fault tolerance.
Build and operate automation for provisioning, deploying, and managing global infrastructure using Infrastructure as Code (IaC).
Improve CI/CD pipelines and release processes to enable safe, fast, and repeatable deployments.
Drive observability best practices, including metrics, logs, traces, and SLIs/SLOs to enable data-driven incident analysis.
Participate in on-call rotations, reducing mean time to resolution (MTTR) through automation and proactive reliability improvements.
Challenge existing processes by championing reliability, security, and operational maturity across the organization.

It starts with you - an engineer driven to build resilient, automated infrastructure that enables teams to move fast with confidence. You care about operational excellence, developer experience, and reliability at scale. Youll architect and operate the compute and networking infrastructure that powers our AI platform - from CI/CD pipelines to Kubernetes clusters to observability systems - across cloud and on-prem environments.
If you want to build infrastructure that powers mission-critical AI systems at national scale, join our companys mission - this role is for you.
The Responsibilities
Architect and operate Kubernetes-based infrastructure across AWS and on-prem environments, ensuring high availability, security, and performance.
Design and maintain CI/CD pipelines for application and service deployments with automated testing, security scanning, and rollback capabilities.
Drive infrastructure-as-code practices for compute and networking - building reproducible, auditable, and version-controlled infrastructure.
Own reliability and incident response - establish SLOs, build alerting systems, lead incident resolution, and drive post-incident improvements.
Enable AI-native operations - support agentic deployment pipelines, self-healing infrastructure, and secure sandboxing for model experimentation.
Build and maintain observability systems - metrics, logging, tracing, and dashboards that provide visibility into system health.
Optimize infrastructure cost and performance - right-size resources, implement auto-scaling, and identify efficiency opportunities.
Collaborate with Engineering, Data Platform, Data Engineering, and Security teams to align infrastructure with platform needs.
Shape infrastructure characteristics that support data freshness, correctness, and low-latency pathways for AI training/inference, retrieval, and agentic workflows.
Contribute paved-road tooling - reusable CI/CD patterns for services, IaC modules for compute and networking, and runbooks - that streamline delivery across teams.
Collaborate with Engineering, Data Platform, Data Engineering, Security, Product, AI/ML, Data Science, and Analytics to anticipate and meet cross-functional needs.

Technical Leadership & Architecture: Drive data infrastructure strategy and establish standardized patterns for AI/ML workloads, with direct influence on architectural decisions across data and engineering teams
DataOps Excellence: Create seamless developer experience through self-service capabilities while significantly improving data engineer productivity and pipeline reliability metrics
Cross-Functional Innovation: Lead collaboration between DevOps, Data Engineering, and ML Operations teams to unify our approach to infrastructure as code and orchestration platforms
Technology Breadth & Growth: Work across the full DataOps spectrum from pipeline orchestration to AI/ML infrastructure, with clear advancement opportunities as a senior infrastructure engineer
Strategic Business Impact: Build scalable analytics capabilities that provide direct line of sight between your infrastructure work and business outcomes through reliable, cutting-edge data solutions
What you'll be doing
Design Data-Native Cloud Solutions - Design and implement scalable data infrastructure across multiple environments using Kubernetes, orchestration platforms, and IaC to power our AI, ML, and analytics ecosystem
Define DataOps Technical Strategy - Shape the technical vision and roadmap for our data infrastructure capabilities, aligning DevOps, Data Engineering, and ML teams around common patterns and practices
Accelerate Data Engineer Experience - Spearhead improvements to data pipeline deployment, monitoring tools, and self-service capabilities that empower data teams to deliver insights faster with higher reliability
Engineer Robust Data Platforms - Build and optimize infrastructure that supports diverse data workloads from real-time streaming to batch processing, ensuring performance and cost-effectiveness for critical analytics systems
Drive DataOps Excellence - Collaborate with engineering leaders across data teams, champion modern infrastructure practices, and mentor team members to elevate how we build, deploy, and operate data systems at scale

We're looking for a Senior AI/MLOps Engineer to join a group that specializes in Security and Networking, and specifically ML, AI and agent development. As a Senior AI/MLOps Engineer, youll build and maintain the infrastructure, tools and processes necessary to support the AI lifecycle in a production environment. You will collaborate closely with data scientists, software engineers, security architects and DevOps teams to ensure smooth deployment, modeling and optimization of AI models. This role involves creative problem solving alongside engineering teams, and is pivotal for the continued success of AI networking security.

What youll be doing:

Developing, improving and optimizing scalable infrastructure for handling and deploying security and networking AI models and agents in production, ensuring high availability, scalability, reproducibility, and performance.

Optimizing AI models and agents for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.

Monitoring and deploying agentic systems, LLMs, and ML models in production.

Designing and implementing frameworks/pipelines for AI training, inference, and experimentation.

Collaborating closely with data scientists, security architects and software engineers to operationalize and deploy AI models and agents, including packaging and integration with existing systems. Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews.

Collaborating with DevOps teams to integrate pipelines and workflows into the CI/CD process, ensuring flawless deployments and rollbacks.

Building and maintaining monitoring and alerting systems to proactively identify and resolve issues relating to quality, performance and infrastructure.

Implementing access controls, authentication mechanisms, and encryption standards for AI models and data.

Documenting guidelines, and standard operating procedures for MLOps/AI processes and sharing knowledge with the wider team.

Develop proof-of-concepts for new features.

We are looking for a Cloud Infrastructure and DevOps Engineer to join our Infrastructure team. Who has a passion for automation, network performance optimization, and high availability infrastructure, who has a desire to design and implement scalable data center solutions with a proactive approach to continuous improvement. We use an interesting and mixed technology stack: Kubernetes, Infrastructure as Code (Terraform/Ansible), and multi-cloud environments (VulTR, DigitalOcean, Linode, Upcloud). In this position you will use your expertise in managing large-scale data center infrastructure and network engineering, and will design, deploy, and maintain high-performance and highly available network and compute infrastructure.
Key Responsibilities
Design, build and manage our cloud infrastructure in order to ensure high availability, scalability, and optimal performance.
Create and maintain Infrastructure as Code (IaC) that deploys, scales, configures, and updates data center equipment, especially network devices.
Monitor network and system performance, detect bottlenecks or connectivity issues, and implement solutions to improve scalability, reliability, and security.
Drive automation and innovation by experimenting with new tools, DevOps best practices, and optimization techniques to reduce operational overhead and accelerate deployments.
Collaborate with cross-functional teams (developers, QA, security, and customer-facing teams) to ensure network security, data integrity, and adherence to industry best practices, while leading knowledge-sharing sessions on infrastructure topics.