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Requirements:
Your Experience
4+ years of experience QA automation developer
Experience in one of the following languages - Python (Must)
Experience with API testing
Experience with cloud-native technologies like DB, Bucket, SQL, GSUITE (SaaS products)
Experience with designing, developing, and implementing test/applicative frameworks from scratch
Deeply passionate about product quality with a mindset focused on continuous improvement
Experience with Gitlab/Jenkins (Advantage).

Requirements:
Bachelor's degree in Computer Science, Cybersecurity, or a related field, or equivalent practical experience.
Strong understanding of modern adversary TTPs and attack methodologies.
Experience with designing and executing simulated attack scenarios in lab environments.
Preferred Qualifications
Proven experience in security research, specifically focusing on SaaS, Identity Providers (IdP), or Cloud platforms.
History of public-facing research, such as conference presentations or blog posts.
Experience with reverse engineering and vulnerability analysis.
Proficiency in one or more programming languages like Python or Go.

Requirements:
Required Qualifications
4+ years of hands-on experience in frontend development
Senior-level experience with modern Angular development - Must
Practical experience using AI-assisted development tools and workflows (such as code generation, debugging, testing, or productivity tools) as part of the daily engineering process.
Solid command of RxJS and reactive programming principles
Extensive hands-on experience with modern Angular frameworks and up-to-date best practices.
Strong understanding of performance optimization, modular design, and scalable architecture
Experience with data visualization or UI animation - Advantage
Independent, proactive, and collaborative team player with strong ownership mindset.

Requirements:
4+ years in security engineering, cloud operations, incident response, threat hunting, DevSecOps, or related security disciplines.
2+ years of hands-on experience securing or operating environments within Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Infrastructure (GCI/GCP).
Strong experience with Kubernetes, containers, and modern cloud-native architectures.
Deep understanding of cloud networking concepts, including VPC Flow Logs, Transit Gateways, service meshes, and traffic patterns (East-West vs. North-South).
Strong comprehension of identity systems (IAM) and how policies interact with network controls to establish secure boundaries.
Experience with CI/CD pipelines and modern software delivery practices.
Proven experience with incident triage, investigations, containment, remediation, or formal operational response processes.
Experience with posture management, governance controls, or applying security best practices such as CIS Benchmarks and recognized cloud architecture frameworks.
Strong scripting or programming proficiency in languages such as Python, Go, or Bash.
Excellent communication skills, demonstrating the ability to clearly explain complex findings and facilitate alignment across cross-functional teams.
Preferred Qualifications
Experience working with large-scale data pipelines and analytics platforms such as BigQuery or Dataflow.
Familiarity with threat frameworks such as MITRE ATT&CK.
Recognized expertise or advanced certifications in cloud security, detection and response, or posture management across Amazon Web Services, Microsoft Azure, or Google Cloud.
Experience operating highly available, large-scale cloud environments.

Requirements:
Required Qualifications
10+ years of hands-on experience delivering production-grade machine learning and deep learning projects at scale.
Proven ability to own the entire lifecycle of a project-taking ambiguous ideas from initial research through to successful production deployment.
Extensive experience designing, training, and fine-tuning complex models, including SLMs and LLMs, tailored to specific proprietary datasets.
Track record of shipping diverse models to production across both resource-constrained endpoints and high-throughput cloud environments.
Deep expertise in building and optimizing agentic AI systems, including RAG architectures and autonomous workflows.
Demonstrated ability to lead technical strategy, ensuring research code is scalable, reliable, and production-ready.
Advanced degree (MSc or PhD) in Computer Science, Machine Learning, Physics, Mathematics, or a related quantitative field.
Excellent communication skills, with the ability to articulate complex architectural decisions to both technical teams and leadership.
Preferred Qualifications
Background in the cybersecurity domain, specifically in developing AI/ML models to detect and prevent cyber attacks.
Deep cybersecurity expertise in non-AI fields, such as vulnerability research, reverse engineering, or low-level security systems development.
Experience with low-level performance engineering, including model quantization, pruning, and runtime frameworks like ONNX or TensorRT.

Requirements:
Required Qualifications
Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
7+ years of professional software engineering experience.
Proven experience building and operating distributed, large-scale cloud products.
Experience in designing, building, and maintaining scalable server-side applications.
Experience with a variety of database technologies such as MySQL, Cassandra, Google BigQuery, Amazon Redshift, or Elasticsearch.
Preferred Qualifications
Experience with writing and maintaining CI/CD pipelines.
Proficiency in Go and/or Python programming languages.
Hands-on experience with Google Cloud Platform (GCP).
Experience with containerization technologies such as Kubernetes and Docker.
Knowledge of the cybersecurity domain and related challenges.

Requirements:
* The Background: Magshimim / Mamriot program trainee or graduate, or equivalent independent cybersecurity research and development experience.
* The Tech: Strong Python skills, hands-on experience building and consuming RESTful APIs, and standard cloud concepts.
* Infrastructure & Servers: Basic knowledge of working with servers and hands-on infrastructure (e.g., computer lab maintenance, hardware/software troubleshooting, or basic system administration).
* The Cyber Edge: Solid understanding of modern attack vectors, vulnerabilities, and security frameworks. You know how to simulate realistic threat vectors.
* The Communicator: You don't just sit behind a screen. You have excellent communication skills, a positive attitude, and the ability to "translate" deep technical engineering concepts into clear, logical stories for product and sales teams. You ask the right questions, collaborate naturally, and aren't afraid to speak up. Key Responsibilities
* Feature & API Integration: Own the end-to-end integration of new product features and capabilities into the company's master demo environment, leveraging and connecting various APIs to ensure smooth data flows.
* Attack Flow Validation: Design, script, and continuously validate realistic cyber attack scenarios and security flows to ensure the demo perfectly highlights our product’s value proposition.
* Environment & Server Maintenance: Maintain, troubleshoot, and optimize the demo infrastructure—including server setups, containers, cloud environments, and scripts—to guarantee 100% uptime and seamless performance during high-stakes client presentations.
* Cross-Team Collaboration: Work closely with Product, Engineering, and Sales Engineering teams to translate complex technical updates into clear, repeatable, and impactful demo scenarios.