דרושים » הנדסה » DevOps Engineer (Agentic Search)

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 are looking for a DevOps Engineer to join our engineering team. The ideal candidate has strong hands-on experience with cloud-native infrastructure, a GitOps mindset, and the ability to independently research and learn new tools and techniques in a fast-moving, large-scale Kubernetes environment.
Responsibilities
Design, operate, and troubleshoot Kubernetes clusters (EKS/AKS) at scale
Manage application delivery and infrastructure using GitOps tools (ArgoCD/Flux)
Build and maintain Helm charts and Kustomize overlays for multi-environment deployments
Provision and manage cloud infrastructure using Crossplane and/or Terraform
Own and optimize CI/CD pipelines (GitHub Actions, GitLab CI) for build, test, and deployment workflows
Maintain and extend observability stacks (Prometheus, Grafana, alerting rules, dashboards)
Write automation scripts and tooling in Python, Go, or Bash to streamline operations
Support AWS infrastructure across multiple accounts/regions (networking, IAM, compute, storage)
Participate in on-call rotation, troubleshoot production incidents, and drive root-cause analysis
Collaborate with platform, security, and application engineering teams on infrastructure design and reliability improvements.

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.
Your Impact:
You'll help scale production systems, improve deployment velocity and reliability, reduce operational overhead, and build automation and AI workflows that help engineering teams move faster and operate more efficiently.
This role is a strong fit for someone who enjoys ownership, collaboration, and operational innovation.

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.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer specializing in infrastructure to join our founding team. The focus of this role is to build and scale the infrastructure that powers autonomous AI agents automating complex enterprise workflows. You will own the systems, pipelines, and platforms that let our AI agents run reliably, securely, and at scale in production.

Your Impact
Infrastructure & Platform

Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.

Build and scale the backend systems that support high-throughput document processing and data extraction workloads.

Cloud Infrastructure and Scalability

Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.

Own containerization and orchestration (Docker, Kubernetes) for all production workloads.

Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.

Data Infrastructure

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.

Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).

API & Systems Integration

Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.

Design for reliability: retries, observability, and graceful degradation across distributed systems.

Security and Compliance

Implement authentication and authorization mechanisms (OAuth2, JWT) to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.

Monitoring and Optimization

Build observability and monitoring systems to track infrastructure health, performance, and cost.

Continuously optimize system performance for speed, reliability, and cost-efficiency at scale.

Collaboration

Work closely with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.

Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

We are looking for a Senior DevOps Engineer who thrives in high-scale, high-performance environments. In this role, you will design and manage mission-critical infrastructure, develop automation tools, and ensure the reliability and scalability of platform. You will work closely with engineering teams to optimize performance, enhance observability, and prevent incidents before they happen.

If you love solving complex infrastructure challenges and building tools that empower engineers, this role is for you!

What Will You Do?
As a Senior DevOps Engineer , you will:

Design, build, and maintain a highly available, scalable, and resilient production infrastructure handling millions of requests per second.
Manage and optimize tens of AWS accounts in a multi-account cloud environment.
Developing AI-driven automation frameworks and tools that more than 400 R&D engineers use while enhancing system reliability and engineering efficiency.
Design, implement, and support the LLM and agentic workflow infrastructure, ensuring its scalability and reliability.
Manage thousands of servers and containers, ensuring seamless infrastructure operations.
Improve and maintain our logging, monitoring, and alerting stacks for enhanced observability.
Troubleshoot and mitigate production incidents, participating in on-call rotations to ensure system health and stability.
Collaborate with engineering teams to optimize performance, reduce latency, and improve deployment processes.

Zipher is building the Autonomous Execution Layer for cloud data and AI workloads. Backed by $50M in funding , we dynamically orchestrate clusters, predict bottlenecks, and auto-heal infrastructure in real time — with zero human intervention . Our platform runs in production at global enterprise customers, including Fortune 500 companies , delivering mission-critical resilience and sub-second optimization We are looking for a DevOps Engineer to build and own the platform our autonomous execution engine runs on. You will own how Zipher ships, scales, and stays up — the delivery pipelines, the Kubernetes infrastructure, and the reliability of systems enterprise customers depend on around the clock.
What You’ll Do

* Architect and own GitOps-based delivery — ArgoCD, Helm, Terraform, GitHub Actions — so the engine ships to production safely, many times a day
* Build and operate the Kubernetes platform , including on-demand environments spun up per pull request and torn down automatically
* Design deployment safety into the platform: canary analysis, blue/green rollouts, automated rollback, and an observability stack (Prometheus, Grafana, OpenTelemetry) that surfaces failure first
* Partner closely with backend and data engineers to make production infrastructure secure, reproducible, and cost-aware across AWS accounts and enterprise deployments
* Drive reliability end to end: define SLOs , own incident response, and raise the operational bar for mission-critical services
What We Offer
* Own the platform behind a new category of autonomous cloud infrastructure High ownership from day one : real architectural influence, direct exposure to founders, and responsibility for mission-critical systems
* A small, technical, high-velocity team that values curiosity, speed, rigor, and engineering craftsmanship Top-of-market compensation and meaningful equity

Ready to own the platform that lets an autonomous execution engine run in production? Hit Apply.

Join a team of senior engineers operating in a large-scale, multi-cloud production environment supporting tens of thousands of enterprise customers worldwide. This is not a typical SRE role - youll work at the core of a complex, high-impact system alongside experienced DevOps professionals in a fast-paced, cybersecurity-focused organization.
Your Impact:
Own and operate large-scale, global production environments across multiple cloud providers (GCP, AWS, Azure)
Actively monitor, investigate, and resolve incidents triggered by automated alerting systems (PagerDuty / Incident Response)
Drive end-to-end troubleshooting across complex, distributed systems with high context switching
Design, deploy, and improve monitoring and observability systems (e.g., Prometheus, Grafana) - not just react to alerts
Collaborate closely with internal teams (CX, CS, Engineering) to ensure system reliability and performance
Work hands-on with modern DevOps and infrastructure tools including Kubernetes, Terraform, CI/CD pipelines, and GitOps workflows
Develop and maintain automation and tooling (primarily in Python)
Gain deep understanding of system architecture and interconnected services
Contribute to a culture of operational excellence in a high-scale, high-availability environment
On call responsibilities:
Daytime hours (12:00-20:00)
Occasional weekends and holidays (rotation-based).

We are looking for a talented and motivated Software Engineer with hands-on experience building and operating multi-agent AI systems in production to join our Automation Platform (DAP) team.
The team develops automation tools, orchestration capabilities, and intelligent platforms that simplify the deployment, management, troubleshooting, and optimization of large-scale network and AI infrastructure environments.
You will work on the design and development of AI-powered systems that bridge networking, automation, observability, and distributed infrastructure - running on Kubernetes at scale. Our stack includes LangGraph, Langfuse, RAG pipelines, MCP, and agent-to-agent (A2A) communication patterns.
This role combines strong software engineering with practical AI application development, with a sharp focus on production hardening, tracing, evaluation, and safety of agentic systems - not model training or research prototypes.

The Role & The Challenge
We are seeking a DevOps Engineer, at the mid or senior level, to join our infrastructure team, reporting directly to our DevOps Team Leader. Depending on experience, this role will either contribute to or help drive advanced infrastructure initiatives - from system design through production hardening - as we raise the bar for operational excellence across the company.
The immediate challenge: our company operates a high-volume, multi-account AWS environment. You will help solve complex delivery, scaling, and operational problems along the way. Scope and ownership will be calibrated to your experience level.
Responsibilities
Contribute to Cloud & Migration Strategy: Work alongside our DevOps Team Leader to help plan and execute our migration from ECS Fargate to Kubernetes (EKS) without downtime, while maintaining our existing cloud estate.
Advance Infrastructure as Code: Design and implement modern, modular IaC frameworks utilizing Terraform and OpenTofu to ensure consistent, multi-environment deployments.
Improve Enterprise CI/CD: Evolve our delivery pipelines (GitHub Actions, OIDC federation) at scale, reducing developer friction and elevating deployment safety across dozens of services.
Support Data-Intensive Infrastructure: Help maintain the performance, capacity, and resilience of our high-volume data layer (ClickHouse, ScyllaDB, DynamoDB, RDS, Redis) and event-driven messaging pipelines.
Strengthen Reliability & Observability: Help maintain organization-wide reliability standards using open, modern telemetry stacks (OpenTelemetry, Coralogix, Grafana), ensuring on-call operations are driven by signal, not noise.
Balance Growth & Governance: Participate in technical tradeoff decisions that balance velocity, least-privilege security, zero-trust access (Tailscale), and FinOps cost efficiency.