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Your Career:
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).

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.
Key Responsibilities
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.

Join our world-class team of researchers and engineers in Tel Aviv, Israel, and play a pivotal role in architecting a more secure foundation for the enterprise browser landscape. This is not just a job; it's a chance to leave your mark on the future of security. Become a pioneer in shaping the core of our Chromium-based enterprise browser and push the boundaries of what's possible.
Your Impact
Lead the change - Own critical features from conception to deployment, shaping the core of our Chromium-based enterprise browser
Mastermind innovations - Solve difficult challenges, keeping our users experience smooth and secure
Empower your team - Mentor and guide fellow engineers, sharing your expertise and fostering a collaborative environment where brilliance thrives
Champion excellence - Set the bar high, driving continuous improvement in processes, tools, and the overall product
Join us and
Work alongside the best in the industry, pushing the boundaries of enterprise security in a collaborative and inspiring environment
Shape the future of a critical product, impacting millions of users and making a tangible difference in the cybersecurity landscape
Grow as a leader and innovator, with unparalleled opportunities to mentor, research, and shape the technical direction of our team.

As a Senior/ Principal/ Senior Principal Software Engineer at Cortex Cloud, you will serve as a primary technical architect and visionary for our core communication infrastructure. This role is focused on the critical server-side backbone that facilitates high-scale bidirectional communication between our cloud services and client-side applications.
You will be responsible for the architectural integrity of systems that receive massive data inflows from the field and reliably broadcast intelligence back to millions of endpoints. This is a high-impact leadership role requiring a blend of deep technical mastery in distributed systems and the ability to influence technical strategy across the organization.
Key Responsibilities
Architectural Strategy & Vision: Define and drive the multi-year technical roadmap for our server-side communication infrastructure, ensuring the platform remains resilient and performant under extreme load.
High-Scale Communication Infrastructure: Lead the design and implementation of backend systems optimized for receiving high-scale data from client-side apps and distributing data back to a vast ecosystem of endpoints.
Technical Leadership & Influence: Act as a force multiplier by providing technical guidance to multiple engineering teams, aligning them on shared protocols, architectural standards, and communication patterns.
Drive Engineering Excellence: Champion a culture of high engineering rigor, focusing on deep observability, low-latency data distribution, and runtime stability for mission-critical production environments.
Cross-Functional Collaboration: Partner with Product Management, Infrastructure, and Client-Side Engineering teams to evaluate technical trade-offs, mitigate risks, and ensure seamless end-to-end data flow.
Innovation & Prototyping: Spearhead the evaluation of emerging technologies and lead "proof of concept" initiatives for next-generation transport layers and messaging paradigms.
Technical Mentorship: Invest in the growth of Senior and Staff engineers through deep-dive design reviews, code audits, and hands-on pair programming on the most critical paths.
Strategic Customer Engagement: Support the business by leading technical deep dives with strategic customers, translating complex architectural concepts into actionable confidence for our partners.

As a DevOps Engineer, you won't just "maintain" infrastructure, you will own it.
You will lead the charge in cloud security automation, using an AI-first mindset to drive extreme efficiency. Your mission is to identify, rectify, and prevent misconfigurations and bottlenecks in advance. You are expected to operate with high autonomy, shaping the future of secure cloud environments by being a proactive force, not a reactive one.
Key Responsibilities:
Innovate & Implement:Design and implement cloud infrastructure solutions with a focus on GCP, including compute reservations, BigQuery, Pub/Sub, GCS, and networking.
Release Engineering: Lead weekly production upgrade cycles across global multi-region environments, including branch-out processes, hotfix management, version gating, and rollback procedures.
Service Deployment & Lifecycle: Own end-to-end service deployments on Kubernetes - from Helm chart creation and Flux/GitOps configuration to production rollout and scaling.
Database Administration:Manage and optimize database infrastructure including MySQL, Redis, BigQuery, Neo4j, Scylla, MongoDB, and PostgreSQL in production environments.
AI Integration: Utilize AI-supporting tools to optimize coding, automate repetitive tasks, and solve complex architectural puzzles. Contribute to AI-native infrastructure such as Vertex AI and AI Gateway services.
Tenant & Customer Infrastructure: Manage customer-specific infrastructure including dedicated compute reservations, tenant provisioning, licensing configuration, and feature flag management across multi-tenant and single-tenant environments.
Infrastructure Automation & Tooling:Develop internal CLI tools and automation scripts (Python) to streamline operations.
Cost Optimization: Drive cloud cost optimization through resource right-sizing, reservation management, database disk reduction, and efficiency improvements.
Service Reliability: Enhance uptime by establishing SLAs, setting up comprehensive monitoring (Prometheus, Grafana, Stackdriver), and participating in the production on-call rotation (including off-hours support).

We are looking for a Senior Staff C++ Engineer to join our Tel Aviv R&D center and take a key engineering role within the Cross Platform Agent team.
Key Responsibilities
Lead the design and implementation of critical Cortex Agent components deployed across endpoint platforms (Windows, macOS, Linux) and cloud-native environments.
Build and maintain high-quality, production-grade software in modern, high-performance C++, owning the full lifecycle from design and implementation through automated test development and production support, including the handling of escalated cases.
Own the ongoing maintenance, hardening, and operational stability of the Defender in cloud-native environments.
Own the reliability and operational stability of the Defender components written in Go (Golang), focusing on production support, incident investigation, root-cause analysis, and hardening in large-scale cloud-native customer environments.
Address complex security, reliability, and performance challenges across large-scale endpoint fleets and distributed cloud environments, including Kubernetes, containers, and container runtimes.
Investigate and resolve complex production and field issues, translating operational insights into scalable, resilient, and efficient system improvements.
Raise the bar on engineering quality by effectively leveraging AI tools in software engineering, leading pragmatic design discussions, conducting focused code reviews, and continuously improving system robustness, correctness, and performance.

we are seeking a Senior or Principal Backend Engineer (we are open to hire both levels) for our Cortex engineering group, focusing on Cortex XSOAR, Cortex XSIAM, and new Cortex AI solutions. In this role, you will design and implement robust backend services for our leading-edge security orchestration, automation, and response platform. You will also contribute to creating innovative AI-based solutions, enhancing shared Cortex infrastructures. This is an exceptional opportunity for those eager to advance Cortex products with AI-driven capabilities and make a significant impact in the cybersecurity industry.
Your Impact:
Own the end-to-end backend development of features and components, from design and development to testing, deployment, and maintenance.
Proactively collaborate and exchange information with peers across different teams and disciplines to shape solutions and ensure alignment on product integrations.
Contribute to team-wide efforts including code reviews, design reviews, and architectural decisions, ensuring high-quality and maintainable code.
Apply a production-oriented approach, providing real-time mitigation and effective solutions to production issues to ensure platform stability and reliability.
Challenge curiously and positively by exploring new technologies and methodologies to enhance our backend services and AI capabilities.

As a Support Enablement and Escalations Engineer on the Cortex Platform team, you will be at the crossroads of Support and Engineering, driving decisions as a thought leader within Global Customer Services. You will work with new products early in their lifecycle, provide training, resolve complex customer issues, and improve product supportability for our industry-leading Cortex products. This role requires excellent cross-functional collaboration with developers, product management, and customers. We seek top-tier candidates from support or engineering backgrounds for our small, impactful global team.
Your Impact
Enable TAC teams by assisting with ad hoc Q&A and providing structured training throughout the year.
Own critical technical issues by identifying widespread problems, creating guidelines, and communicating updates to relevant teams.
Impact new product development by defining supportability and usability requirements during design and post-release enhancement phases.
Develop and deliver technical training materials for TAC, such as white papers and presentations, on new products.
Develop internal tools for the TAC team to improve visibility and streamline troubleshooting processes.
Analyze support cases, trends, and escalations to identify and address knowledge gaps, supportability issues, and tooling needs.
Proactively identify and execute on unplanned projects that improve customer experience, reduce costs, or bolster security.

As the Software Engineering Director, you will lead backend engineering teams and groups dedicated to building and maintaining our industry-leading cybersecurity. You will define and drive the vision and strategy for software development, ensuring the highest delivery standards of quality, security, and scalability. In close collaboration with product management, platform teams, you will guide the delivery of innovative, reliable solutions that address the evolving needs of our customers and safeguarding our clients data within the dynamic cloud landscape.
Key Responsibilities
Lead and mentor BE engineering teams and managers, driving recruitment, retention, and talent development. Foster a culture of collaboration and innovation
Oversee the design and delivery of secure, scalable software solutions, ensuring best practices in security throughout the development lifecycle
Work closely with product, design, and platform teams to align engineering with business goals and customer needs
Drive innovation by designing and implementing impactful solutions that address client needs, contributing to the full feature development lifecycle from design to deployment
Take ownership of wide feature segments, ensuring high-quality code and robust functionality through meticulous attention to detail and a focus on execution
Proactively collaborate and exchange information with cross-functional teams, including product and infrastructure, to ensure seamless integration and alignment on shared objectives
Engage in technical discussions, openly sharing knowledge and learning from others to solve complex problems and elevate team expertise
Design and build highly scalable, resilient, and secure cloud-based applications and microservices.

As a Senior or Principal Software Engineer in Cortex Cloud, you will contribute to the development and scaling of cloud-native security solutions for enterprise organizations. This role involves working within an established team to evolve a high-traffic product, with a focus on refining architecture, optimizing the technology stack, and maintaining engineering standards.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools: Utilize platforms such as Gemini, Claude, and Cursor for tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows: Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards: While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents: Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.

As an ML Software Engineer with a focus on low-level and CUDA-based optimizations, you will play a key role in shaping the design, performance, and scalability of machine learning inference systems. Youll work on deeply technical challenges at the intersection of GPU acceleration, systems architecture, and ML deployment.
Your expertise in CUDA, C/C++, and performance tuning will be crucial in enhancing runtime efficiency across heterogeneous computing environments. Youll collaborate with designers, researchers, and backend engineers to build production-grade ML pipelines that are optimized for latency, throughput, and memory use, contributing directly to the infrastructure powering next-generation AI products.This role is ideal for an engineer with strong systems-level thinking, deep familiarity with GPU internals, and a passion for pushing the boundaries of performance and efficiency in machine learning infrastructure.

Responsibilities
Design and implement highly optimized GPU-accelerated ML inference systems using CUDA and low-level parallelism techniques
Optimize memory, compute, and data flow to meet real-time or high-throughput constraints
Improve the performance, reliability, and observability of our inference backend across diverse compute targets (CPU/GPU)
Collaborate with cross-functional teams (including researchers, developers, and designers) to deliver efficient and scalable inference solutions
Contribute to ComfyUI and internal infrastructure to improve the usability and performance of model execution flows
Investigate performance bottlenecks at all levels of the stack-from Python to kernel-level execution
Navigate and enhance a large, complex, production-grade codebase
Drive innovation in low-level system design to support future ML workloads

As a Senior DevOps Engineer supporting our Cortex Research Group, you will lead all DevOps and infrastructure initiatives that empower our researchers to move quickly, securely, and reliably. You will be responsible for designing, building, and maintaining the groups cloud environments, ensuring scalability, stability, and performance across a wide range of experimental and production workloads. Youll serve as the primary point of contact between the Research Group and other critical stakeholders-including Security, Networking, and Compliance teams-ensuring that research projects align with organizational standards while still enabling rapid innovation.
Key Responsibilities
Own and evolve the Research Groups cloud infrastructure and CI/CD pipelines to enable reproducible, automated, and scalable experimentation.
Define and implement standards for infrastructure-as-code, observability, monitoring, and resource optimization tailored to research use cases.
Proactively collaborate with security and compliance teams to enforce best practices for data governance, access controls, and regulatory requirements.
Partner with networking and platform engineers to integrate research workloads into the broader company ecosystem, ensuring seamless operation.
Serve as the primary technical liaison between the Research Group and stakeholders like Security, Networking, and Platform teams.
Mentor engineers and researchers on DevOps best practices, helping to instill a culture of operational excellence and applied learning.

As a Large Scale Training Engineer, you will play a key role in enhancing the training throughput of our internal framework and enabling researchers to pioneer new model concepts. This role demands excellent engineering skills for designing, implementing, and optimizing cutting-edge AI models, alongside writing robust machine learning code and understanding supercomputer performance deeply. Your expertise in performance optimization, understanding distributed systems, and bug elimination will be crucial, as our framework supports extensive computations across numerous virtual machines.

This role is designed for individuals who are not only technically proficient but also deeply passionate about pushing the boundaries of AI and machine learning through innovative engineering and collaborative research.

Key Responsibilities
Profile and optimize the training process to ensure efficiency and effectiveness, including optimizing multimodal data pipelines and data storage methods.
Develop high-performance TPU/GPU/CPU kernels and integrate advanced techniques into our training framework to maximize hardware efficiency.
Utilize knowledge of hardware features to make aggressive optimizations and advise on hardware/software co-designs.
Collaboratively develop model architectures with researchers that facilitate efficient training and inference.
Design, maintain, and evolve a high-quality, shared codebase that emphasizes correctness, readability, extensibility, testing, and long-term maintainability, while balancing performance requirements.

As a Large Scale Video Understanding Research Scientist, you will play a key role in improving video generation quality and efficiency by improving video and audio understanding pipelines used for both training data construction and model evaluation.. This role demands hands-on work with large-scale Video Language Models (VLLMs), including fine-tuning, post-training, and control, alongside implementing classic computer vision and signal processing algorithms and applying strong research skills. Your expertise in post-training and controlling large scale foundational models, understanding statistics, implementing complex systems and eliminating bugs will be crucial, as our video training sets consist of petabytes of data processed across hundreds to thousands of virtual machines.

What you will be doing
Fine-tune and control VLLMs for video and audio understanding.
Design algorithms for balancing, filtering, and curating training and evaluation datasets, informed by model behavior and failure modes.
Implement classic and modern algorithms for processing, clustering, evaluation and filtering of large scale datasets.
Work within high-performance, scalable distributed systems capable of handling petabytes of data, with attention to throughput, correctness, and reproducibility..
Collaborate with other researchers and product stakeholders to iteratively improve training sets and evaluation protocols through tight feedback loops driven by model performance.

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.