our company's platform runs inside the security stacks of enterprise customers, processing live detection and telemetry data from SIEM, EDR, and SOAR systems at real scale. Until now, infrastructure has been built and carried by the founding engineering team alongside everything else. You will be the first dedicated owner of it. That means designing our company's cloud foundation across GCP and AWS, building the deployment, scaling, and observability layers from the ground up, and setting the standards the rest of engineering builds on. It also means holding a bar that most startups can defer and our company cannot: we sell to security teams who audit their vendors seriously, so how we run our own infrastructure is part of how we win. This is a hands-on senior role with real architectural authority, and as engineering grows you become the person others learn cloud and infrastructure from.
What you'll be doing
Multi-cloud architecture: Own the design and implementation of our company's multi-cloud architecture across GCP and AWS, including the cross-cloud standards, boundaries, and tradeoffs that keep two providers from becoming twice the complexity.
Infrastructure as code: Build and maintain the entire environment in Terraform, so infrastructure is reviewable, reproducible, and scales without a person in the loop.
Deployment pipelines from scratch: Create the CI/CD foundation that lets a small team ship quickly and safely, with the testing, gating, and rollback paths that make fast releases boring rather than risky.
Kubernetes at data scale: Run and scale the Kubernetes and containerized workloads behind our company's security data processing, where volume, latency, and cost pressure all show up at once.
Security of our own stack: Own identity, access, secrets, network boundaries, and infrastructure hardening to a standard that holds up under customer security review.
Reliability and visibility: Build the logging, monitoring, and alerting layer that tells us something is wrong before a customer does, and make on-call sustainable as the system grows.
Technical direction: Partner directly with the founding engineering team on architectural decisions, and raise the infrastructure and cloud fluency of every engineer who joins after you.

Were looking for a DevSecOps Manager to lead our Israel-based DevSecOps team and own the security posture of our cloud infrastructure. Youll inherit a strong, established team of DevOps and DevSecOps engineers with meaningful ownership and a mature security program.
This is a hands-on leadership role that combines people management, technical depth, and architectural influence. Youll define the cloud security roadmap, remain close to the code and systems, and partner with Product Security, R&D, and Cloud Engineering to make security part of the platform by default.
Youll own:
The security posture of our multi-cloud infrastructure across AWS, Azure, and GCP.
Identity governance, least-privilege access, credential lifecycle management, and cloud vulnerability management.
Security controls embedded directly into the cloud platform, enabling R&D teams to build and operate securely by default.
Developer toolchain security, including CI/CD pipelines, software supply chain risks, and developer-facing guardrails.
The implementation of security as code, replacing manual processes and ticket-based controls with scalable automation.
The leadership, development, and technical growth of a team of DevOps and DevSecOps engineers.
Teams roadmap, priorities, and quarterly planning in alignment with Cloud Engineering and the broader Security organization.
The teams role as the primary cloud security partner for Product Security, R&D, and Cloud Engineering.
Clear security standards, ownership boundaries, and operating practices across the cloud platform.
Youll solve:
Security challenges across a large, evolving environment with multiple production cells, several cloud providers, and more than 500 engineers.
Gaps in cloud identity, permissions, credentials, workload protection, and vulnerability management.
Security risks within Kubernetes, including RBAC, pod security, network policies, and runtime protection.
Risks across GitHub, CI/CD pipelines, third-party dependencies, and the software supply chain.
Friction between strong security controls and the speed, usability, and autonomy R&D teams need.
Repetitive security work by turning manual controls into automated, reusable platform capabilities.
Cross-functional challenges that require alignment between Cloud Engineering, Product Security, R&D, and compliance stakeholders.
Emerging cloud security gaps by proactively identifying them, proposing practical solutions, and driving remediation through completion.

Our platform turns paperwork-based processes into revenue-generating customer engagements for some of the largest financial institutions in Israel, the US, Europe, and APAC.

Behind that surface, our infrastructure is split the way our customers are. Enterprise customers demand isolation and get it: a dedicated single-tenant environment each, down to their own compute, data stores, identity provider, and sometimes encryption keys we cannot access. Lower-tier customers run on shared multi-tenant infrastructure. More than fifty production environments across six AWS regions, all from one GitOps pipeline.

That split is what makes this role heavy. On the shared platform, a single change is instantly global; on the dedicated fleet, it must land correctly everywhere before anyone feels it. Every new customer adds load and cost in a straight line - your job is to break that line, making the platform carry its own weight through self-service, automation, and AI agents, not more hands. Nobody sits between you and the customer.

Responsibilities

Both tenancy models, as one system. Terraform, Helm, and ArgoCD delivering to shared and dedicated environments alike. You own the pipeline and the guardrails on it: progressive rollout, blast-radius containment, and drift detection that catches a mistake before a customer does.
Efficiency and cloud cost. Dedicated infrastructure per customer makes unit economics an engineering concern, not a quarterly finance exercise. You own attribution, right-sizing, spot strategy, and autoscaling that actually scales down - and you defend efficiency as a design constraint on every new deployment.
Turning operations into product. Onboarding, version rollouts, and config changes are tickets today; they should be self-service and boring. You decide what gets automated, what goes back to the owning team, and what still needs an expert.
Scale under real load. Temporal, KEDA queue-based autoscaling, and Karpenter are live and still maturing. You own how the platform grows and shrinks against real traffic, and what that costs per customer.
Security engineering for regulated customers. KMS-based key management, SIEM pipelines, WAF policy, certificate and secret lifecycle, per-customer SSO, vulnerability remediation, and turning penetration test findings into shipped fixes. Our customers are banks, insurers, and health funds. Their auditors are effectively part of our roadmap.
AI-driven operations. Our infrastructure repositories are already built for agentic work, with an internal harness of shared skills and agents. You inherit it, extend it, and push it into places it does not reach yet: triage, rollout verification, cost anomaly investigation, log analysis, and the long tail of operational work that has never been worth a script.
Reliability of what you ship. You are on call for your own systems, paged through PagerDuty against alerts you own.

We're hiring a Senior/Principal Site Reliability Engineer to own production reliability for Cortex Agentix Endpoint Security (following an acquisition of KOI Start Up) as it scales. You'll define and operate our SLOs and error budgets, lead high-severity incident response, and ensure our Kubernetes and AWS infrastructure stays stable under growth. You'll also build and supervise the AI agents that handle routine alert triage and monitor tuning, focusing your own time on the reliability engineering that requires human judgment. This role is a strong fit for someone who treats reliability as an engineering discipline and enjoys ownership, incident command, and applying AI to operational work.
Your Impact:
Own reliability as an engineering discipline - define SLIs, set SLOs, and run error-budget-based decision-making so "how reliable are we" becomes a number that governs how fast we ship.
Own production incidents end-to-end - lead response, mitigation, and resolution for high-severity incidents, and drive blameless postmortems that feed real fixes back into the system.
Own the reliability and capacity of production infrastructure as we scale - forecasting headroom, validating scaling behavior under load, and keeping latency and error rates within SLO.
Run and evolve Kubernetes environments so releases and infra changes are safe by default across hundreds of tenant apps.
Own, build, and supervise our SRE AI agents that triage alerts, review monitors, resolves and summarize incidents. Set and expand the trust ladder that governs what the agents do autonomously, what needs approval, and what stays human. This is a core part of the role.

What You'll Do
Platform and infrastructure (K8s + IaC).
Architect and operate our Kubernetes platform on AWS - scaling, networking, cost, and reliability.
Own infrastructure as code (Terraform) so environments are reproducible, auditable, and fast to evolve.
Build the foundations that let the team provision and scale services without friction.
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AI agent platform - managing and scaling agents at volume
Operate and scale the orchestration layer (Temporal) that runs dozens of agents in parallel.
Tune the platform for the unusual load profile of agent workloads - bursty, long-running, data-heavy, latency-sensitive.
Give engineers the primitives to deploy, version, observe, and roll back agents safely under enterprise SLAs.
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CI/CD and developer experience.
Own build and deploy pipelines end-to-end - fast, safe, boring releases.
Invest in DX as a first-class product: the team treats developer experience as leverage, and you set the bar.
Reduce the time from merged to in production and from idea to running experiment.

Observability and reliability
Build monitoring, alerting, and tracing that make production legible - for services and for agents.
Own incident response and the reliability practices that keep enterprise customers SLAs intact.
Turn incidents into systemic fixes, not repeated firefighting.

Security and compliance
Own secrets management, hardening, and the day-to-day security posture of the platform.
Support our compliance commitments (we are Mastercard-certified, operating in fintech - the bar is high).
Build security into the pipeline so it is the default, not a gate.
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Tech is at the center of everything we do and we're looking for people who are builders at their core. From developers to visionaries and everything in between, we want minds who aren't just interested in putting the pieces together but who can find new ways to innovate. Solid communication, creative problem solving and business understanding are all prerequisites. So, if you're tech savvy, inquisitive, and ready to take the road less traveled, the Technology team might be right for you. We're looking for a Senior DevOps Engineer with a strong security orientation to join our DevOps team. our platform runs at significant scale, and our DevOps team sits at the core of keeping it fast, reliable, and secure. As we grow, so does the scope of what we own - we need an engineer who can step in as a strong pillar of our production ecosystem. This is a hands-on role for someone who takes security seriously, moves fast, and knows how to get things done in a complex, high-scale environment. Our Technology Stack: AWS, GCP, CLoudFlare,Kubernetes, Terragrunt, Ansible, Jenkins, ArgoCD, Argo Workflows, Kong & Nginx, HashiCorp Vault, Kafka, RabbitMQ, Mongodb, Aurora Postgresql & Mysql, Prometheus, Grafana, VictoriaMetrics Programming languages: Python, NodeJS, Go, Kotlin


What am I going to do?:

* Full Ownership: Drive infrastructure initiatives through their entire lifecycle, taking accountability from initial design to delivery and long-term operations.
* Kubernetes Orchestration: Architect, implement, and maintain production-grade Kubernetes clusters, ensuring they remain scalable and resilient under high-scale demand.
* Cloud Architecture: Design and manage robust AWS environments, including VPC, IAM, and EKS, to support a highly available platform architecture.
* Infrastructure as Code: Utilize Terraform to build and evolve our environment, applying configuration management principles to all IaC workflows.
* CI/CD Excellence: Support and improve our deployment pipelines using Jenkins and GitHub Actions to maintain a fast development velocity.
* Observability: Implement comprehensive monitoring solutions with Prometheus and Grafana to ensure deep visibility into platform health.
* Operational Resilience: Join the DevOps on-call rotation, taking responsibility for mitigating production issues and maintaining site reliability.
* Tooling & Innovation: Continuously evaluate and adopt tools - security and otherwise - that raise the bar on engineering efficiency and security posture.
Equal opportunities:
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. We prioritize diversity. We celebrate difference and embed it into every aspect of our workplace and product, as well as our community. We are 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, we will provide accommodation to individuals with disabilities or a special need.

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.

We're looking for an all-round infrastructure engineer who writes production-grade code, designs systems from first principles, and owns everything from infrastructure-as-code to a multi-cloud ML serving stack. You'll be joining a small, elite infrastructure team that owns it all.


What you will do
Lead infrastructure architecture across the company and take end-to-end ownership across our infrastructure - cloud environments, platform tooling, internal services, and production uptime.
Design and build production-grade services and internal platform tooling; you write code at the same bar as the product engineering team.
Operate and scale AI/ML Serving Infrastructure systems behind real-time LLM routing, model inference, and AI security enforcement in production.