דרושים » הנדסה » Low-level Quality Lead

We are looking for an experienced manager to drive the development of our cloud sensor - the industrys most efficient security tool for monitoring application-layer attacks in real time.

What youll be doing:

As the sensor group lead, you will be responsible for leading several teams of highly skilled low-level engineers. This group is responsible for developing the sensor, which is deployed in customer environments to monitor their applications in real time for detecting and blocking cyber attacks in cloud environments. You will drive the development of innovative, scalable, and high-quality capabilities in our sensor, while maintaining low overhead and high performance.

You will:

Lead the technological vision of our sensor, overseeing the full development lifecycle, including design, implementation, testing, deployment, rollout, and validation.
Take an active part in design decisions, leading the sensor architecture to maintain high performance, scale and enterprise grade quality.
Lead a group of low-level engineers, build efficient processes, provide mentorship to drive high performance, recruit strong talent, and ensure strong development velocity.
Collaborate closely with research, engineering, and customer-facing teams , turning innovative security concepts into reality.

We are looking for a detail-oriented and technically skilled Senior QA Engineer to join our engineering team and help ensure the quality, reliability, and security of our product.
In this role, you will own the quality of complex cybersecurity features from design through production, working closely with developers, product managers, and automation engineers. You will play a key role in defining test strategies, identifying risks early, and ensuring high-quality releases.
As part of your daily workflow, you will leverage AI-powered tools to improve test planning, discover edge cases, investigate defects, analyze logs, and enhance overall testing efficiency.
The Responsibilities:
Own the automation domain end-to-end: strategy, architecture, implementation, and continuous improvement
Design, build, and maintain scalable test automation frameworks across UI, API, integration, and system layers
Develop hands-on automation code in Python and/or TypeScript
Drive quality standards across engineering teams, partnering closely with developers, QA, DevOps, and product stakeholders
Define and implement automation best practices for reliability, scalability, maintainability, and fast feedback
Integrate and optimize automation within CI/CD pipelines to enable rapid, confident releases
Test complex SaaS, cloud, and cyber-related product flows, including security-sensitive scenarios, permissions, integrations, and system behavior
Use AI tools to support automation development, test generation, debugging, log analysis, documentation, and coverage improvement
Proactively identify coverage gaps and improve system testability, observability, and debuggability
Participate in system design and feature planning to embed quality from the earliest stages
Build and evolve testing environments using scripting, infrastructure-as-code, and cloud-native tools
Mentor and guide engineers, elevating automation standards across the organization

As a Senior Low-level Software in our Sensor team, you will design, implement, and optimize cutting-edge software that runs within our clients' environments and monitors their applications accurately and efficiently. Youll have the opportunity to tackle complex technological challenges, research new technologies and build innovative solutions in the Linux system realm. In particular:

Design, Plan and implement efficient and reusable code that drives complex applications
Research innovative solutions that set our Application Security approach apart
Optimize performance and resource consumption in challenging environments
Lead complex projects in close collaboration with Product Managers and other Software Engineers
Interface and collaborate with other R&D teams to deliver end-to-end solutions

Were looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all our company engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI at our company, covering agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. You will lead a high-impact team of 5 engineers to create the runtime and platform that defines the future of autonomous enterprise intelligence.
Youll Own:
Agentic Framework Architecture: Designing and building our companys internal agentic framework, leveraging and integrating industry-standard tools such as LangChain, LangSmith, ADK, and similar ecosystems.
Evaluation and Quality Systems: Building evaluation frameworks and workflows for AI agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
Team Leadership & Mentorship: Leading a squad of 3-4 senior engineers, fostering a culture of technical excellence, and managing end-to-end delivery in a fast-paced environment. You will spend approximately 50% of your time hands-on, architecting core systems and reviewing code, and 50% leading the team, mentoring engineers, and aligning with cross-functional stakeholders.
Observability, Monitoring, and Guardrails: Providing the organization with robust observability capabilities for AI agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer Enablement Platforms: Creating APIs, SDKs, and abstractions that enable product teams to easily build, test, and operate agents while adhering to platform standards.
Cross-Language Integrations: Designing integrations and tooling across Python and Java to enable seamless adoption of the AI framework within our companys broader backend ecosystem.
Youll Solve:
Agent Lifecycle and Orchestration Complexity: Managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
AI System Reliability at Scale: Ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
Evaluation and Drift Challenges: Detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
Platform Adoption Friction: Balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.
Youll Impact:
Company-Wide AI Enablement: Empowering every engineering team at our company to build agent-based solutions faster, with higher quality and confidence.
Foundational AI Infrastructure: Establishing the core frameworks, evaluations, and observability standards that all AI agents at our company will rely on.
AI Safety and Quality Bar: Raising the bar for how AI systems are evaluated, monitored, and governed across the company.

we are looking for a Senior Software Engineer to join our Core Engineering group. The group is responsible for the real-time, low-latency infrastructure that powers fraud decisions and external APIs.

Our systems process billions of requests every day, ensuring high availability, security, and performance at global scale.

In this role, youll work on core backend components such as our decision engine, ingestion and enrichment pipelines, schema management systems, and self-serve API platform. The software you build will power critical business decisions and directly serve some of the worlds largest merchants.

This is a high-impact, high-ownership position for an engineer who thrives on solving complex distributed systems challenges, cares deeply about production-grade quality, and wants to shape the foundation of decisioning platform.



What you'll be doing:

Design, build, and scale backend systems that power real-time decisioning and APIs.
Own projects end-to-end - from design and implementation to production rollout and monitoring.
Ensure systems are low-latency, fault-tolerant, and high-throughput across distributed environments.
Enhance observability, reliability, and developer experience through strong operational and tooling practices.
Collaborate with Product, analysts, data scientists, and infrastructure teams to drive innovation across decision ecosystem.
Participate in technical discussions and customer interactions, providing expertise and clear communication when supporting enterprise integrations.

Join us and become a key leader in building the most innovative endpoint security solution in the world. Our sensor development team is responsible for building the endpoint sensor which deploys on multiple platforms including Windows, Mac, and Linux. As a Software Engineer, you will be expected to have ownership over major components and development projects. You will be required to assist with architecting solutions and support in implementing our core features. Features will cross-cut most core OS subsystems such as file system, memory and process, and networking. Many features are also built in a way that they will have shared components across multiple platforms. You need to be able to lead projects efficiently while maximizing performance and minimizing costs, making sure high standards are being followed when it comes to design, coding quality, and unit and component testing.


What You'll Do:
You will be joining the Identity protection team that delivers detection and prevention of identity related incidents in the organizational network using the falcon sensor and cloud. You will work with an experienced team of capable developers and participate in establishing the Israeli R&D center of one of the most innovative and exciting software companies in the world today.
In this role you will be responsible for building an efficient lightweight sensor for Active Directory servers. You will participate in implementing the next generation of CrowdStrikes world-leading Identity Protection technology.

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.

we are looking for a Senior DevOps Engineer Platform Engineering.
Responsibilities:
-Design, build, and operate the internal engineering platform powering ' build, test, deployment, and security validation workflows at scale
- Write and maintain production-grade Python and shell tooling that drives platform automation - this is a hands-on coding role, not just pipeline configuration
- Architect and manage hybrid cloud/on-prem execution infrastructure, including large-scale Kubernetes runner pools across multiple AWS regions
- Own and evolve CI/CD pipelines at scale using GitHub Actions, including reusable workflows, ARC-based runner orchestration, and build caching strategies (BuildKit, sccache, Valkey)
-Operate and tune DinD environments (Sysbox, EBS/NVMe, overlay storage, MTU/networking) for build, test, and release workloads
- Connect and manage self-hosted and on-prem runners, routing physical device (wbox) test jobs by site and device type
- Implement DevSecOps controls including least-privilege IAM, OIDC, isolated runner groups, container signing, and automated security scans
- Drive platform observability, cost optimization, and reliability improvements across the engineering infrastructure
- Collaborate cross-functionally with hundreds of engineers to improve engineering velocity and release confidence
- Take end-to-end ownership of complex infrastructure problems and drive them to resolution

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.