דרושים » תוכנה » Senior DevOps Engineer, AIOps

We are seeking an experienced DevOps Engineer to join our Engineering team and play a key role in building and operating our cloud-native platform. The ideal candidate will have hands-on experience managing production environments at scale, driving cloud transformation initiatives, and supporting the of enterprise systems from on-premises deployments to modern SaaS and cloud-native architectures. You will be responsible for designing, automating, and maintaining scalable infrastructure, CI/CD pipelines, and deployment processes that support both our core products and emerging AI-driven capabilities. Working closely with Engineering, QA, Product, and AI teams, you will help ensure the reliability, security, and performance of our services while driving operational excellence and continuous improvement across our technology stack.
Responsibilities:
Design, implement, and maintain CI/CD pipelines.
Manage and optimize cloud infrastructure across AWS, Azure, and/or GCP.
Develop and maintain Infrastructure as Code using Terraform.
Manage Kubernetes-based environments and GitOps deployment workflows using Argo CD and Kustomize.
Lead and support the migration of enterprise applications and infrastructure from on-premises
environments to scalable SaaS and cloud-native architectures.
Establish, maintain, and continuously improve production environments, ensuring high availability, security, scalability, and operational excellence.
Demonstrate strong production ownership, including incident management, root cause analysis, capacity planning, and performance optimization.
Collaborate with Engineering, QA, Product, and AI teams.
Support the deployment, operation, and monitoring of AI and Generative AI services.
Build and maintain monitoring, logging, and alerting systems.
Troubleshoot and resolve infrastructure, deployment, and production issues.

We're looking for a Senior Platform Engineer to join our CTI Group. We're a startup that builds a lot, so you'll work across a wide range of systems and tools, build new platforms and services, and have real influence over where the platform goes next.
You'll work on the platform behind our CTI products: the microservices running on Kubernetes, the cloud and on-prem environments around them, and the infrastructure behind the systems. There's a lot still to build, and you'll have a real say in what comes next.
Responsibilities
Own what you build end to end, from design through implementation to running it in production.
Design and build the internal platforms, tools, and services other engineering teams rely on, and add new ones as we grow.
Make architectural decisions across infrastructure, applications, networking, security, and data.
Design, build, and maintain our cloud and on-prem environments.
Build and operate the infrastructure behind our AI/ML systems at scale.
Manage and evolve our Kubernetes environments.
Build and maintain CI/CD pipelines, deployment automation, and Infrastructure-as-Code with Terraform.
Build security into the platform, from IAM and secrets management to network policies.
Set up the monitoring and observability that show us how the platform is doing.
Design for scalability, availability, performance, and resilience in high-scale production systems.
Apply Infrastructure-as-Code practices (Terraform) end to end.

we are a leader in large-scale networking solutions for AI infrastructure and service providers. The company's disaggregated networking architecture transforms the economics of large-scale infrastructures while maximizing performance, utilization, and operational efficiency. Its high-performance AI fabric maximizes GPU utilization and accelerates deployments by optimizing the AI stack end-to-end, resulting in higher tokens-per-second and lower cost-per-token. our company's solutions power production networks for global tier-1 operators like AT&T and Comcast, and scale multi-vendor AI infrastructures at foundation model labs, NeoClouds, and enterprises.
our company's Cybersecurity business unit is building an AI-powered security platform for the world's largest service provider networks. The platform combines a cloud-native microservices backend with self-hosted LLM inference, delivered into customers' own Kubernetes environments - often air-gapped, with no data leaving their premises.
Responsibilities
Own the platform's Helm charts and make them portable across any Kubernetes distribution, including OpenShift (non-root, restricted SCCs, NetworkPolicies).
Operate the self-hosted operator stack: CloudNativePG, Strimzi, ECK, MinIO, Redis, and Temporal.
Run the Nx monorepo pipelines and drive the ArgoCD GitOps rollout.
Build zero-downtime releases using blue/green and canary deployments, expand/contract migrations, and automated rollback.
Manage autoscaling with KEDA/HPA, backup/restore for stateful services, and load-validation of stamp sizing tiers.
Provide on-call support for dev/staging environments and customer stamps.
Build and maintain observability using Grafana Alloy, OpenTelemetry, and Prometheus/Grafana - dashboards and alerts across services, Kafka, databases, and GPUs.
Improve developer experience through a shared dev cluster with local-debug traffic interception (Telepresence / mirrord), targeting sub-15-minute onboarding.

We are seeking a highly skilled DevOps / Platform Engineer to join our R&D team. In this role, you will be responsible for designing, operating, and scaling our cloud infrastructure while supporting both engineering and machine learning initiatives.

You will own our AWS environment end-to-end - from infrastructure architecture and Kubernetes operations to MLOps enablement, security hardening, and cost optimization. This role goes beyond traditional DevOps and includes responsibilities across IT operations support, multi-account AWS management, DevSecOps practices, DevFinOps ownership, and machine learning infrastructure.

You will play a critical role in ensuring our systems are secure, scalable, observable, and cost-efficient, while enabling fast and reliable software and model delivery.

Responsibilities
Cloud Infrastructure & Platform Ownership

Design, implement, and maintain scalable infrastructure in a multi-account AWS organization
Manage and deploy applications using Helm charts, GitOps workflows using ArgoCD
Support CI/CD pipelines and release processes.
Observability & Reliability

Implement and maintain monitoring and logging solutions.
Define alerts, dashboards, and SLOs to ensure system health and operational excellence.
MLOps Enablement

Support and operate ML infrastructure in AWS
Enable reliable model deployment, monitoring, and lifecycle management.
DevSecOps & Security

Implement security best practices across infrastructure and CI/CD pipelines
Enforce IAM least-privilege policies and secure networking configurations
Integrate security ownership and compliance controls.
DevFinOps & Cost Optimization

Monitor and optimize AWS resource utilization and costs
Implement cost visibility and reporting practices
IT & Operational Support

Support internal IT-related infrastructure tasks
Continuously improve operational processes and automation

As a Senior Site Reliability Engineer at our company 911, you'll own the infrastructure that keeps our platform reliable, scalable, and secure - work that directly supports mission-critical 911 systems used by public safety agencies. You'll drive infrastructure-as-code practices across AWS, lead observability efforts through Datadog, and bring modern AI-assisted engineering approaches into how the team builds and operates.
What You'll Do
Own and evolve AWS infrastructure using Infrastructure-as-Code (Terraform / Terragrunt)
Architect and scale AWS environments
Deploy, scale, and manage containerized workloads using Kubernetes and Docker; contribute to HA/DR architecture and platform strategy
Lead deployment and release processes using Argo (reference JD also names Bitbucket, Jenkins as part of the CI/CD toolset).
Define and enforce SLOs, SLIs, and error budgets; drive toil reduction across the platform
Drive full utilization of Datadog for monitoring, dashboards, and alerting across the platform (reference JD also names Prometheus, Grafana as potential observability tooling)
Build self-service internal developer platforms that empower teams to ship faster.
Take end-to-end ownership of infrastructure projects - define success criteria, execute, and measure outcomes.
Partner cross-functionally with engineering teams (e.g., network engineering, Dev owners) on long-term technical planning.
Bring AI-assisted engineering practices (e.g., Claude, MCP integrations) into daily workflows to improve team efficiency
Document work and provide cross-training to peers.
Resolve JIRA tickets across Cloud, CI/CD, deployments, and monitoring.

Responsibilities
- Design, build, and operate the internal engineering platform powering our company's build, test, deployment, and security validation workflows at scale
- Write and maintain production-grade Python and shell tooling that drives platform automation - this is a hands-on coding role, not just pipeline configuration
- Architect and manage hybrid cloud/on-prem execution infrastructure, including large-scale Kubernetes runner pools across multiple AWS regions
- Own and evolve CI/CD pipelines at scale using GitHub Actions, including reusable workflows, ARC-based runner orchestration, and build caching strategies (BuildKit, sccache, Valkey)
- Operate and tune DinD environments (Sysbox, EBS/NVMe, overlay storage, MTU/networking) for build, test, and release workloads
- Connect and manage self-hosted and on-prem runners, routing physical device (wbox) test jobs by site and device type
- Implement DevSecOps controls including least-privilege IAM, OIDC, isolated runner groups, container signing, and automated security scans
- Drive platform observability, cost optimization, and reliability improvements across the engineering infrastructure
- Collaborate cross-functionally with hundreds of engineers to improve engineering velocity and release confidence
- Take end-to-end ownership of complex infrastructure problems and drive them to resolution.

We are on an expedition to find an On-Premise Site Reliability Engineer (SRE)- someone who is passionate about building rock-solid, high-performance infrastructure and bringing order to complex environments. In this role, you will own the end-to-end reliability, automation, and deployment of our platform across customer sites, working hands-on with cutting-edge AI, bare-metal, and hybrid cloud architectures.
Youll collaborate closely with Product, R&D, and Architecture teams while serving as the ultimate technical authority for our customer deployments. From designing automated Ansible workflows and mastering Kubernetes to troubleshooting complex network topologies, you will eliminate toil, streamline cluster operations, and ensure every deployment is scalable, seamless, and mission-ready.
Responsibilities
Lead End-to-End On-Prem & Hybrid Deployments: Own the technical delivery and reliability of our platform in close collaboration with Product, R&D, and customer technical teams.
Architect, Execute & Improve K8s Deployments: Take a definitive hands-on role in deploying, configuring, operating, and continuously improving our platform using advanced, enterprise-grade Kubernetes architectures.
Helm Chart Management: Design, modify, and manage Helm charts to package, version, and streamline complex application deployments across different environments.
Drive Automation & Simplification: Design, implement, and maintain robust deployment automation using Ansible. You must have a passion for turning complex manual tasks into reliable, repeatable, single-click operations.
Manage Infrastructure as Code: Utilize Git as the single source of truth to manage configurations, manifests, and automation playbooks, enforcing modern engineering best practices.
Bridge On-Prem and Cloud: Leverage AWS resources (specifically EC2 and S3) for hybrid components, staging environments, or cloud-to-on-prem data flows.
Technical Tier-3 Escalation: Serve as the ultimate technical authority for deployment, Linux networking, and Kubernetes orchestration issues.
Continuous Improvement: Constantly refine our delivery pipelines, optimize bootstrap processes, and create rock-solid technical documentation.

Required DevOps Engineer
About the role:
Our DevOps team operates the infrastructure that powers our AI and Computer Vision platform across construction sites in 15+ countries. From data pipelines and ML workloads to backend services - you'll work with a diverse, modern, Kubernetes-based stack and have real influence on how we build, deploy, and operate.
What you'll do:
Own Multi-Cloud Infrastructure: Work alongside the team to design, scale, and operate our high-scale, multi-region production infrastructure across AWS and GCP, powering construction sites globally.
Drive Kubernetes at Scale: Manage and evolve our Kubernetes platform on EKS and leveraging GitOps practices with ArgoCD and Helm to enable safe, fast, and reliable deployments.
Build Robust CI/CD: Design and maintain CI/CD pipelines that empower dozens of engineers to ship confidently - with automation, testing, and progressive delivery built in.
Tackle Diverse Infrastructure Challenges: Work hands-on with a wide variety of workloads - from heavy data processing and Computer Vision pipelines to backend services and ML inference - each with unique scaling, performance, and reliability requirements.
Ensure Reliability & Observability: Build and maintain world-class observability (metrics, logs, tracing, alerting) so that issues are caught early and resolved fast. Performance, reliability, and scalability are at the core of what you do.
Security & Cost: Partner with the team to strengthen our security posture, identity and access management, compliance, and cloud cost optimization across both clouds.
Ownership from 0 to 1: You will have real influence over our architecture and tooling. We want engineers who care about shaping what we build and how we build it, ensuring performance, security, and observability are baked in from day one.

Your Career:
Own and continuously improve AWS production infrastructure for scalability, reliability, security, performance, and cost.
Run and evolve Kubernetes environments that support fast, safe product delivery.
Drive developer velocity and production safety through better CI/CD pipelines, release workflows, deployment visibility, and GitOps practices.
Improve observability and incident response - reduce alert noise and raise signal quality.
Design and ship AI-assisted operational agents that change how engineers work - triaging monitoring alerts, summarizing incidents, proposing fixes, onboarding new services, answering questions and requests. This is a core part of the role, not a side project.
Build automation and self-service tooling that removes manual work from provisioning, monitoring, incident response, and developer workflows.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, inefficiencies, and automation opportunities.
Partner with engineering, security, product, and leadership to remove bottlenecks and support safe production growth.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.

We are constantly striving to make our systems reliable, scalable, and simple to operate so our services are available to travelers when they need them most. With our continued growth, we have exciting challenges ahead and we're looking for a Senior Site Reliability Engineer to join our team in Tel Aviv. This role blends classic SRE ownership with pragmatic AI SRE work: you will build and operate the platforms, automation, observability, and incident response practices that keep Navan reliable, while helping teams use AI solutions, AI providers, and their APIs safely and dependably.



This is a hands-on engineering role, not a research role. You will partner with product, platform, data, security, support, and incident response teams to make production systems and AI-powered experiences more resilient. You will use software engineering, infrastructure as code, SLOs, telemetry, provider observability, and automation as your main tools, and you will apply AI where it creates measurable reliability value rather than novelty.



This position is based out of our new Tel Aviv office.



What You'll Do:

Support AI-based application solutions where reliability matters. Partner with the development teams building AI-powered travel experiences to support the development and production operation of their solution.
Work with AI solutions, providers, and APIs. Partner with teams integrating AI capabilities and providers, with attention to API reliability, authentication, quotas, rate limits, latency and provider-specific operational constraints.
Troubleshoot AI tools and provider issues. Diagnose failures across AI-powered workflows, provider APIs, configuration, permission errors, degraded responses and related areas.
Operate reliable production platforms. implement and run cloud infrastructure,and help product teams move quickly without compromising reliability.
Improve observability. Build dashboards, alerts, traces, logs, and runbooks that make service health clear, actionable, and tied to SLOs and customer impact.
Apply AI to SRE workflows. Prototype and productionize AI-assisted systems that create effective and efficient operations
Automate operational toil. Create tools, workflows, and automation that remove repetitive manual work and make operational knowledge easier to use.