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06/05/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for an Engineering Manager to lead the frontend development of the XSOAR & Agentix team within the Cortex Platform. You will be joining a fast-moving group developing advanced solutions in one of our companys most innovative and technically complex areas.
We are not just looking for a standard engineering manager. We are seeking an AI-Native leader - someone who lives and breathes AI, combines hands-on technical depth with managerial excellence, and knows how to wield AI as a massive force multiplier for their team.
Responsibilities
AI-Driven Team Leadership: Lead, mentor, and grow a team of frontend engineers. You will embed AI-first coding methodologies into the team's DNA, moving beyond basic usage to systemic adoption of automated testing, intelligent code reviews, and code generation.
Technical Strategy: Drive the frontend architecture for our Automation platform.
You will oversee the design of complex interfaces that manage advanced playbooks and automated incident response workflows.
Accelerated Delivery and Quality: Drive the timely achievement of roadmap goals. Utilize AI coding assistants and cutting-edge workflows to dramatically quicken delivery while simultaneously boosting architectural integrity and code quality.
Cross-Functional Collaboration: Partner closely with Product Management, UX, and Backend engineering to translate complex security automation requirements into intuitive, seamless user experiences.
The AI-Native Leadership Profile
Visionary and Strategic Execution
You possess a clear, forward-looking thesis on how AI will transform software engineering over the next 2-3 years, and you are adept at executing against this vision.
Practical AI Implementation
You are a builder, not just a user: you have successfully designed and implemented AI-driven development workflows that your previous teams actively adopted.
Continuous Experimentation
You are an active experimenter, constantly testing new AI tools, LLMs, and prompt engineering techniques, and integrating the best of them into daily engineering operations.
Requirements:
Required Qualifications
5+ years of hands-on software engineering experience, with deep expertise in modern Frontend or Full-Stack development.
2+ years of direct experience managing and scaling software engineering teams.
Proven AI adoption: A track record of adopting AI coding tools to accelerate development cycles, generate boilerplate, and optimize code logic.
Technical Depth: Hands-on, senior-level expertise with Angular or React, and TypeScript/JavaScript.
Strong understanding of frontend performance optimizations, modular design, and scalable architecture for distributed systems.
Preferred Qualifications:
Experience building custom AI agents or workflows specifically tailored for development teams.
Background in cybersecurity, Security Orchestration, Automation, and Response (SOAR).
Experience with complex data visualization and managing high-scale web applications.
B.Sc. or M.Sc. in Computer Science, Software Engineering, or equivalent practical/military experience.
This position is open to all candidates.
 
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06/05/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
Are you an AI Analyst ready to translate raw model output into a reliable, high-quality production system? Do you excel at the craft of Prompt Engineering and thrive on the challenge of ensuring Generative AI output meets rigorous quality standards in mission-critical applications? Join our R&D Operations Team. You will be the AI analyst responsible for the end-to-end quality, performance, and operational tuning of our Generative AI-driven support system (Co-Pilot). Your mission is to actively shape the model's intelligence, govern the data it uses, and implement the mechanisms that guarantee its accuracy, directly accelerating our customer support engineering velocity.
Key Responsibilities
Support & Customer Advocacy: Champion the Support Journey in Engineering. Develop in-product support instructions that reflect and address real incoming cases, enhancing the quality and effectiveness of AI feature solutions.
Model Quality Validation: Use existing evaluation platforms and methodologies to validate production models. Monitor quality metrics to continuously assess and rank AI answers for accuracy and reliability.
Prompt Engineering & CT Loop: Drive the Continuous Training loop through systematic prompt engineering (refining and versioning inputs). Analyze failures to define R&D actions or features needed to close model performance gaps.
AI Knowledge Governance: Act as AI Content Governor, implementing controls to verify and ingest compliant knowledge base content, ensuring a quality data source.
Cross-Functional SME: Serve as the AI Support Co-pilot Subject Matter Expert, partnering with R&D and Support Enablement to translate quality issues into core model logic improvements and feature development.
Requirements:
Minimum of 5+ years of professional experience in a blend of technical and analytical roles (e.g., Automated QA, Support Enablement, Data Analysis,AI Research. Prompt Engineering, MLOps), with a proven track record operating at the critical intersection of customer operations, data management, and AI/ML systems
AI/ML/LLM Foundation: Possesses a high-level understanding of AI tools, LLMs, machine learning, and applicative AI principles.
Python Proficiency: Proficient in Python for practical applications, including scripting, data processing, and building automation solutions.
Customer Domain Mastery: Demonstrated experience in customer-facing roles with a strong operational understanding of the Customer Support domain (workflows, knowledge base management, optimization).
Technical Communication: Strong skills in translating observed model performance issues and Agentic Action requirements into clear, prioritized technical requirements for R&D teams.
Ownership: A dedicated individual who takes full responsibility for their work, driving projects to successful completion.
Data/Content Governance: Experience with data validation, content management, and implementing data governance standards, especially for knowledge bases feeding AI systems.
Preferred Qualifications
Prompt Engineering: Proven expertise in systematically authoring, testing, and refining instructional inputs to drive specific model behavior.
Cloud Technologies: Experience with Cloud platforms like GCP, Kubernetes and containers
CI Pipelines using Gitlab
Experience with BigQuery
Experience working with APIs.
This position is open to all candidates.
 
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