דרושים » תוכנה » DevOps Architect

As a Senior DevOps Engineer within the XSPM team, you will be a critical, go-to technical expert responsible for the health, performance, and evolution of our database and infrastructure systems. When production databases degrade or behave unexpectedly, you are the person who dives deep, investigating root causes hands-on, understanding the underlying mechanics of the problem, and designing lasting solutions. Your mastery of database systems makes you the authority the team relies on to diagnose complex performance issues, architect better data solutions, and ensure our infrastructure scales with confidence.

Beyond databases, you will drive our DevOps practices end-to-end - CI/CD pipelines, infrastructure automation, and operational reliability across the XSPM platform. This is a high-impact, highly visible role at the intersection of database engineering and DevOps, where your expertise directly shapes how the team delivers and operates at scale.

We're a highly collaborative, friendly, inclusive and diverse group that prizes collaboration over competition. We provide opportunities to learn new skills, mentor fellow engineers, and contribute to the direction of both the team and the products for which we're responsible. We work in a distributed, high-trust environment where you manage your own time and have the flexibility to balance your work and personal life.

What You Will Do:

Serve as the team's database expert, the first person to investigate, diagnose, and resolve complex performance problems across our production database systems (MongoDB, OpenSearch, PostgreSQL, Cassandra).

Perform deep-dive root cause analysis on database performance issues, understanding query execution internals, resource consumption patterns, cluster behavior, and system-level interactions to identify the real source of problems, not just symptoms.

Design and propose better database architectures and solutions, recommending when to re-architect data models, migrate workloads, introduce new technologies, or redesign how services interact with their data layer.

* You will put in every effort within the team to ensure the data architecture is well designed.

Own capacity planning, scaling strategies, and high-availability designs for database clusters, ensuring systems are built to handle the team's growth trajectory.

Act as the bridge between development and infrastructure, advising engineers on how their application patterns impact database performance and guiding them toward sustainable solutions.

Build and maintain CI/CD pipelines, infrastructure-as-code (Terraform, Helm, Kubernetes manifests), and automated deployment workflows for the xspm team's services.

Design and manage observability stacks, dashboards, alerting rules, and SLOs, to maintain best-in-class availability for critical data pipelines and services.

Drive infrastructure automation to reduce operational toil, including automated scaling, self-healing systems, and configuration management.

Participate in on-call rotations, incident response, and post-incident reviews, driving root-cause analysis and long-term reliability improvements.

Evaluate and adopt new database technologies and infrastructure tooling that align with the team's evolving data architecture needs.

We are looking for an experienced SRE Team Lead to drive the reliability, observability, and automation practices across our private cloud infrastructure and operations. In this role, you will lead a team of site reliability engineers, own the engineering roadmap for monitoring and automation, and act as a key liaison between development, operations, and platform teams. You bring at least 3-4 years of hands-on people management experience and a deep technical background in SRE or DevOps disciplines.



What will you do?

Leadership & Team Management

Lead, mentor, and grow a team of SREs, providing technical direction, career development guidance, and day-to-day management.

Own the team roadmap for reliability, observability, and automation initiatives - prioritizing work, removing blockers, and driving delivery.

Conduct regular 1:1s, performance reviews, and hiring processes to build and sustain a high-performing team.

Foster a culture of operational excellence, blameless post-mortems, and continuous improvement.

Act as an escalation point for complex incidents and reliability issues, leading post-incident reviews and ensuring follow-through on action items.


Automation & Infrastructure

Design, develop, and maintain automation tools to support infrastructure and operations teams at scale.

Manage pipelines and infrastructure workflows using Jenkins, Ansible, Python, and Bash.

Drive the adoption of infrastructure-as-code practices across the organization.

Collaborate with system engineers to improve scalability, performance, and fault tolerance of critical systems.


Monitoring & Observability

Build and extend monitoring and alerting systems using Grafana, the ELK (Elastic) stack, Zabbix, and custom scripts.

Implement and enforce observability best practices to ensure full visibility into systems, applications, and infrastructure.

Define and track SLIs, SLOs, and error budgets across key services.

Partner with development teams to embed observability earlier in the software development lifecycle.


Database & Platform Support

Support monitoring and infrastructure integration for databases including MongoDB and PostgreSQL.

Maintain documentation and champion knowledge sharing around automation, monitoring, and reliability practices.

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.

You will manage the AI Platform Engineer(s), set the technical standards for the AI Power User group's citizen development program, and serve as the connective tissue between business leadership, platform owners, and development teams. You will shape the multi-year AI architecture roadmap while also rolling up your sleeves to conduct architecture reviews, resolve blockers, and move use cases from concept to production. This is a role for someone who can think big and execute - and who understands that in an enterprise context, the quality of your governance is inseparable from the quality of your architecture.
What You'll Own
Strategy & Architecture
Define and own the enterprise AI integration strategy - identifying opportunities to embed intelligent automation, agentic workflows, predictive analytics, and generative AI capabilities across our core platforms
Develop and maintain reference architectures, design patterns, and the AI architecture decision log that governs how AI models connect to enterprise systems and what they are permitted to do
Consult on enterprise system architecture and implement best practices for the Enterprise Business Systems team to leverage in their day-to-day execution.
Lead Proof-of-Concept initiatives for new AI tools and platform-native AI features, evaluating them against build-vs-buy criteria before recommending adoption
Partner with business stakeholders to translate operational pain points into AI use cases with clear ROI framing and sequencing criteria
Contribute to our enterprise data strategy, ensuring AI initiatives are supported by clean, accessible, and well-governed data pipelines
Integration Architecture & Delivery

Design and own the Workato eMCP layer - the MCP governance model, persona-scoped token framework, workspace isolation strategy, and the single sanctioned action surface through which all AI agents write back to enterprise systems
Define integration patterns and standards for AI model connectivity (Claude, ChatGPT) to Salesforce, NetSuite, HiBob, and Jira - specifying what agents can read, what they can write, through which surfaces, and with what confirmation and audit requirements

We are looking for an experienced Sr. Principal Architect to join the XSIAM engineering group in a highly cross-functional, product-facing role. This position sits at the intersection of engineering, product management, customer success, and product architecture, helping shape scalable and innovative solutions across the XSIAM product.
The ideal candidate combines deep technical expertise with strong product thinking, enabling them to translate business and customer needs into clear architectural direction and execution strategies. This role requires close collaboration with engineering teams, product managers, and strategic customers to drive platform capabilities, integrations, scalability, and long-term architectural vision.
Key Responsibilities
Lead architectural design and technical strategy for XSIAM platform capabilities and integrations.
Define best practices, technical standards, and scalable design patterns across the organization.
Work closely with customers, field teams, and support organizations to understand real-world use cases and pain points.
Evaluate tradeoffs between scalability, performance, security, operational complexity, and delivery timelines.
Support strategic customer engagements and complex deployment scenarios.
Mentor engineers and technical leaders on architecture, system design, and product-oriented engineering thinking.
Act as the bridge between engineering, product, and site reliability (SRE) to ensure that architectural designs translate into operational excellence.

We are looking for a talented Architect to join us. As a Data Architect, you will be the organizational point of contact for all things related to data persistence and architecture. You will work closely with engineering teams across the Product, Platform, and Data groups to design, govern, and evolve our data models, databases, and data-related systems. Your goal will be to ensure scalability, reliability, security, and efficiency for all data storage and retrieval across the organization.
A few of the things you will do:
Be the primary point of contact and subject matter expert for data persistence across the entire engineering organization.
Define and govern the data architecture strategy, standards, and best practices for relational, NoSQL, and data warehouse systems.
Partner with engineering teams from product, platform, and data groups to design and implement scalable and robust data models for new and existing services.
Lead the design and optimization of the organizations data flows. You will help to ensure that data moves efficiently, consistently, and with high quality across all systems and domains.
Evaluate and recommend new technologies and data solutions to meet evolving business needs.
Drive initiatives to improve data quality, consistency, and integrity across all production systems, from ideation to hands-on execution.
Establish, maintain, and communicate documentation for all data models and architectural decisions.

we are seeking a Hands-on Architect to design, build, and evolve the core of next-generation AI cybersecurity platform.This is not an ivory-tower role; it is for a builder at heart. You will write code, build functional prototypes, and own critical services from inception to production. This role demands a unique blend of deep, code-level execution with a broad, system-wide architectural vision that spans our entire data, cloud, and AI stack.
Responsibilities:
Rapidly code and build functional proofs of concept (PoCs) and prototypes to explore and validate new architectures, data platforms, data processing frameworks, and GenAI capabilities.
Validate technical feasibility, scalability, and business impact through working software, not just diagrams or documents.
Partner closely with engineering, product and data science teams to translate emerging technologies into production-ready, scalable systems.
Lead architecture design reviews, proactively identify scalability and performance bottlenecks, and embed security principles into the design process from day one.
Serve as a technical leader and mentor, elevating the team's skills through pair programming, in-depth code reviews, and deep-dive sessions on system design and software craftsmanship.

We're seeking a Staff engineer - AI Builder to lead the design and implementation of AI-native technical frameworks that redefine how large-scale systems are built, extended, and evolved.
This role is deeply technical and architecture-driven, focused on designing modular, extensible, and AI-first system foundations that enable scalable development with AI as a core engineering collaborator.
You will work across the full stack, building infrastructure where AI actively generates, extends, and maintains software components as part of the native development flow.
This is not about incremental AI integration - this is about architecting the frameworks that let AI scale software engineering 10x faster and smarter.
Responsibilities
Architect and lead the development of AI-native system frameworks that emphasize modularity, extensibility, and adaptive scalability.
Build platform primitives that enable dynamic AI-driven module and extension generation.
Design and implement developer workflows optimized for AI-assisted software development, embedding AI collaboration as a first-class design principle.
Define and codify AI-native engineering practices, patterns, and guidelines to elevate our software development lifecycle.
Establish and champion best practices for AI-assisted engineering across system design, code quality, testing, observability, and operational scalability.
Drive hands-on prototyping and iterative delivery across frontend, backend, and orchestration layers.
Provide technical leadership and mentorship, fostering an AI-first engineering culture across teams.
Partner closely with Product, AI, and Engineering teams to align system evolution with AI-native goals.

We are seeking a skilled and motivated DevOps engineer with deep familiarity in the streaming ecosystem to join our elite infrastructure team. If you're excited by the challenge of operating mission-critical systems at scale and optimizing the developer experience through automation and tooling, wed love to hear from you.

What you will do:

Automate Deployment and Operation
Oversee deployment of Kafka and RabbitMQ clusters (including Confluent Cloud & CFK). Build automation pipelines to ensure repeatability and resiliency across environments.

Monitor and Support Production Systems
Own production stability of global Kafka clusters. Handle on-call rotations, incident management, troubleshooting, and scaling challenges.

Improve Infrastructure Observability
Build and maintain observability systems: dashboards, alerting pipelines, metrics collection (Prometheus, Grafana, etc.).

Optimize System Performance
Collaborate with peers on benchmarking and optimization initiatives. Work on tuning Kafka brokers, cluster configurations, and runtime parameters.

Provide Developer Support and Training (Infra-focused)
Help developers configure topics, quotas, and consumers appropriately. Train service owners to interpret monitoring data and avoid pitfalls.

Develop and Maintain Infrastructure
Contribute to building infrastructure tools and scripts (IaC, Helm charts, etc.) that make provisioning and managing clusters reliable and efficient.

Secure Infrastructure Access
Configure and maintain secure access patterns across streaming infrastructure, ensuring proper authentication and role-based access controls are enforced for both developers and services.

We are looking for an experienced SRE Engineer to drive the reliability, observability, and automation practices across our private cloud infrastructure and operations. In this role, you will be in a team of site reliability engineers, own the engineering roadmap for monitoring and automation, and act as a key liaison between development, operations, and platform teams. You bring at least 4+ years of hands-on people management experience and a deep technical background in SRE or DevOps disciplines.

What will you do?

Automation & Infrastructure
- Design, develop, and maintain automation tools to support infrastructure and operations teams at scale.
- Manage pipelines and infrastructure workflows using Jenkins, Ansible, Python, and Bash.
- Drive the adoption of infrastructure-as-code practices across the organization.
- Collaborate with system engineers to improve scalability, performance, and fault tolerance of critical systems.

Monitoring & Observability
- Build and extend monitoring and alerting systems using Grafana, the ELK (Elastic) stack, Zabbix, and custom scripts.
- Implement and enforce observability best practices to ensure full visibility into systems, applications, and infrastructure.
- Define and track SLIs, SLOs, and error budgets across key services.
- Partner with development teams to embed observability earlier in the software development lifecycle.

Database & Platform Support
- Support monitoring and infrastructure integration for databases including MongoDB and PostgreSQL.
- Maintain documentation and champion knowledge sharing around automation, monitoring, and reliability practices.