דרושים » תוכנה » Senior Software Engineer Runtime Internals

As a Software Engineer - Scraping Specialist, youll build the systems that power how AI interacts with the live web. Youll design and implement large-scale, intelligent web acquisition pipelines, making sense of an ever-changing online ecosystem and transforming it into structured, high-quality data.

This role blends technical understanding of browsers, networks, and automation with hands-on engineering. Youll work on adaptive systems that navigate modern websites, understand evolving web interaction ,detection systems, and gather meaningful information safely, efficiently, and at scale.

Your work will directly shape ability to provide AI agents with accurate, real-time knowledge of the world , bridging the gap between the open web and intelligent reasoning.

What Youll Do
Build distributed data acquisition systems that capture and structure the live web
Investigate and analyze browser internals, fingerprinting, and anti-automation systems to develop stealthy, adaptive orchestration layers
Prototype and deploy intelligent automation frameworks using Playwright, Puppeteer, and low-level browser control protocols (CDP)
Conduct hands-on research into network flows, JavaScript-based protections, and emerging web standards affecting automation
Collaborate with AI and infrastructure teams to integrate real-time web data into retrieval pipelines and LLM-powered agents
Translate deep technical insights into production-grade components, balancing research freedom with engineering rigor
Continuously evolve capabilities in resilience, speed, and authenticity of web interaction

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 asGemini, Claude, and Cursorfor 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 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 asGemini, Claude, and Cursorfor 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 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 asGemini, Claude, and Cursorfor 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 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 asGemini, Claude, and Cursorfor 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.

We are looking for a Sr. Staff Security Engineer to be a technical anchor on this team.
Security R&D operates in two complementary modes: open contribution to product engineering - writing code alongside product teams where security expertise adds value - and developing its own security capabilities, including internal tooling, externally facing product features, AI-powered security automation, and third-party integrations.
This is a new team being stood up in Petah Tikva, Israel, co-located with our AI Security Research team. You will be one of the senior technical leaders shaping the teams engineering culture, architecture decisions, and technical direction from its inception.
This role reports to the Sr. Engineering Manager, Security R&D.
What You Will Do:
Lead Technical Design and Architecture:
Drive architecture and design decisions for Security R&Ds capabilities, ensuring systems are built for enterprise scale, reliability, and maintainability.
Lead technical design reviews and serve as the senior engineering voice on security tooling, automation, and platform services built by the team.
Define technical standards, code quality expectations, and engineering best practices for the Security R&D team.
Evaluate and integrate third-party security services alongside in-house AI-powered capabilities to maximise security review coverage.
Build Security Capabilities at Platform Scale:
Design and develop security tooling, automation, and platform-native services - both for internal use and as externally facing product features.
Contribute code directly into our product engineering codebases where security domain expertise accelerates delivery and improves security outcomes.
Leverage our unique platform advantages - Agent Framework runtime, ACL enforcement, data layer, and workflow engine - to build capabilities that external vendors cannot replicate.
Collaborate with the AI Security Research team on AI agent security tooling, bringing production engineering discipline to an emerging domain.
Mentor and Elevate the Team:
Mentor junior and mid-level engineers, raising the technical bar across the team through code reviews, design guidance, and hands-on pairing.
Represent Security R&D in cross-functional discussions with product engineering leadership, demonstrating technical credibility as an engineering peer.
Contribute to hiring by helping define the technical interview bar and participating in candidate evaluations.

We are hiring an AI Researcher to join the research team building the next generation of AI-native security systems. You will work alongside security and threat researchers to build large-scale AI agents that reason over software, code, endpoint activity, and security signals to detect malicious behavior, uncover vulnerabilities, assess risk, and make autonomous security decisions in real-world production environments. We are entering the Mythos era - where attackers operate at machine speed using autonomous systems and AI-generated software, and defenders must evolve the same way. We use state-of-the-art frontier models, including access to Mythos, to build reliable AI-native security systems at global scale. You will help design the evaluations, harnesses, and reliability infrastructure that make autonomous agents dependable under real customer load, while collaborating with leading AI organizations including Anthropic on initiatives such as Glasswing. This is an opportunity to work at the frontier of AI, autonomous systems, and cybersecurity while helping define how the next generation of security systems will operate.
Key Responsibilities
Build AI agents and autonomous security systems that reason over software, code, endpoint activity, MCPs, and security signals to detect malicious behavior, uncover vulnerabilities, and assess risk at production scale.
Develop systems, tooling, and infrastructure that enable agents to autonomously investigate threats, hunt for malware in massive datasets, and operate reliably in complex security environments.
Design and run experiments to evaluate frontier-model and agent capabilities in realistic adversarial scenarios, including benchmark creation, large-scale datasets, automated evaluations, and human-in-the-loop review systems.
Build the evaluation harnesses, observability systems, and reliability infrastructure required to make autonomous agents accurate, scalable, and dependable under real customer load.
Engineer for scale and performance across large distributed AI systems, including inference optimization, orchestration, batching, caching, cost controls, and graceful degradation under high demand.
Continuously evaluate emerging models, agent architectures, prompting techniques, and research directions to ensure our systems remain at the frontier of AI-native cybersecurity.
Rapidly prototype and test new approaches across reasoning, autonomy, evaluations, and security workflows as the AI landscape evolves.
Partner closely with threat and security researchers to extract domain expertise, translate analyst reasoning into AI workflows, and enable new forms of automation and autonomous investigation.
Collaborate with leading AI and security researchers to shape the future of AI-native cybersecurity as the industry transitions into the Mythos era.
Senior candidates will help define research direction, shape technical strategy, identify high-leverage problems, and influence how autonomous AI systems are deployed across the organization.

We are looking for an experienced QA engineer to lead and drive the Quality of our cloud sensor - the industrys most efficient security tool for monitoring application-layer attacks in real time.

we are a fast-growing cybersecurity startup transforming how organizations protect their applications, cloud environments, and AI systems at runtime. Backed by top-tier investors including Greenfield Partners, Red Dot Capital Partners, Lightspeed, Ballistic Ventures, and TLV Partners, were on a mission to make real-time security a reality.

As our Sensor Quality Lead, youll own the quality of the Sensor - how we test it, and how we prove it works accurately and efficiently across the environments our customers run it in. There's no existing playbook for this role; you'll be the one writing it, tackling complex testing challenges in the Linux systems realm and building the automation that lets us ship with confidence.

In particular:

Design and build automated test frameworks and specialized harnesses for the Sensor
Build and maintain test environments across Kubernetes, Docker, and VMs, including test applications written in different languages, so a single build is validated everywhere it runs
Build the test infrastructure that measures accuracy, performance, and resource consumption under high scale
Define quality metrics for the Sensor, build the test infrastructure that measures them along with dashboards and visibility measures to surface them
Collaborate with the Sensor teams, Product Managers, research, and other R&D teams to deliver end-to-end quality

Required Senior Software Engineer
About the role
As a Senior Software Engineer on the KSPM team, you will join a mission-critical group building and scaling one of the companys core and fastest-growing security products. Our team enables customers to secure their Kubernetes environments across every major cloud provider, delivering deep visibility into cluster misconfigs, RBAC risk, admission control, compliance drift and container vulnerabilities.
In this role you will design the backend services and data models that discover, onboard, scan, and represent K8s workloads, APIs, and configurations at scale. You will own core services end-to-end, drive architectural improvements and partner with security researchers to turn complex threat vectors into actionable insights.
We are looking for backend engineers who care deeply about software design, cloud-native infrastructure, and container security. This is a high-impact role with real ownership - lead features end-to-end, mentor teammates, and help shape the technical direction of our KSPM offering.
Our Stack: Python, Go, K8s APIs, K8s ecosystem tooling (OPA/Gatekeeper, admission controllers), Docker & container runtimes, SingleStore, Postgres, Redis, Kafka, SQS, ElasticSearch, AWS, GCP, Azure.
On a typical day youll:
Design & build at scale: Design, implement, and maintain scalable backend services that discover, onboard, scan, and analyze Kubernetes environments across multi-cloud and managed clusters.
Model K8s security: Map and represent Kubernetes resources as clean data models that surface misconfigurations, exposure risks, and compliance violations.
Integrate detection engines: Integrate and evolve detection engines for container vulnerabilities, secrets, RBAC risks, misconfigurations, and compliance frameworks.
Collaborate on research & product: Partner with security researchers and product managers to translate novel findings and complex requirements into impactful features.
Design for quality: Write clean, well-tested code in Python or Go, with thoughtful abstractions and APIs that keep the system correct and maintainable as it grows.
Lead & mentor: Lead design discussions and code reviews that uphold high engineering and security standards across the team.
Own it end-to-end: Own features through their full lifecycle - from technical specification and design through implementation, testing, and release.

Were looking for exceptional Senior Engineers who take full ownership of their work-from technical design through implementation and into real-world usage. This is a hands-on role for individuals who bring strong engineering fundamentals, curiosity across the stack, and a high standard for quality and reliability.
Youll join a team that values autonomy, deep thinking, and the ability to navigate both frontend and backend challenges. We expect engineers to care about how their systems behave in production-not just whether they compile-and to help build reliable, scalable software that stands up to real-world demands.
What Youll Do
Design, implement, and ship end-to-end features spanning web, mobile, backend, and infrastructure layers
Tutor, guide and help to nurture a culture of technical excellence throughout the development organization
Own your code through its lifecycle-from spec and architecture to deployment, monitoring, and evolution
Investigate and resolve issues that arise in staging or production, and help build tools that make doing so easier
Work closely with product and design to define technical solutions that deliver real user impact
Improve system architecture, performance, and development practices over time
Collaborate with peers through code reviews, design discussions, and shared ownership of technical quality