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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.
Your Impact
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.

Your Career:
The Cortex Content team powers Palo Alto Networks security operations platforms (XSIAM/XSOAR) by building the essential integrations, data connectors, and intelligence layers that protect our customers.
We are looking for a Senior Software Engineer who is passionate about AI and automation to help scale our content ecosystem. In this role, your focus will be leveraging AI to accelerate the delivery, quality, and quantity of our security integrations and content infrastructure. You will design and develop intelligent tools and workflows that enable engineering peers and Technical Program Managers (TPMs) to scale their output, collaborating with them as they test, adopt, and integrate these solutions into our development lifecycle.
Your Impact:
Scale Content Delivery: Design and implement AI-driven systems that empower the team to significantly increase both the quantity and the rigorous quality of our security integrations.
Develop Cross-Functional Tooling: Build internal developer tools and agentic workflows that enable other engineers and TPMs to streamline content creation, validation, and management.
Optimize Workflows: Create reliable CI/CD pipelines incorporating AI agents to automate code generation and testing processes.
Support Team Adoption: Collaborate with engineering peers and cross-functional partners as they test and integrate your tools into their daily workflows, using their feedback to drive continuous improvements.
Contribute to AI Integration: Help lead the practical integration of LLMs and automation frameworks into our day-to-day engineering processes.

We are looking for a Principal MLOps Engineer with a deep focus on ML Platforms and Infrastructure to join our Data & AI group at Cortex Research. Our team is responsible for designing, building, and scaling the foundational MLOps and LLMOps platforms that power both our Data Scientists and Security Researchers. You will architect the high-performance core infrastructure that enables these roles to build, train, and deploy advanced AI systems-ranging from optimized Small Language Models (SLMs) to complex agentic workflows and RAG systems. If you are passionate about building scalable compute platforms and automating the full ML lifecycle to solve complex data and security challenges, we want to hear from you.
Key Responsibilities
Scale Distributed Training: Design and optimize infrastructure for training and fine-tuning LLMs and SLMs, leveraging distributed GPU workloads, efficient clustering, and compute optimization.
Automate the ML Lifecycle: Architect robust, automated pipelines for continuous training (CT) and deployment (CD) of models, ensuring a seamless flow from raw data collection to production environments.
Build Model Infrastructure: Own the serving architecture for LLMs/SLMs, balancing latency, throughput, and GPU utilization under production traffic.
Implement Advanced Monitoring: Establish comprehensive observability systems to monitor live model performance, data drift, and computational metrics, feeding insights back into the automated training loops for continuous improvement.
Collaborative Architecture: Partner closely with data scientists and security researchers to productize complex model architectures and streamline their workflows, while collaborating with our DevOps team to integrate with core cloud infrastructure.

We are establishing a new role focused on bridging AI capabilities with our internal DevOps platform. You will build AI-powered tools and services that run on top of the DevOps platform developed by the infrastructure team. This role combines hands-on DevOps/platform engineering work with close collaboration with software development teams, enabling them to build, deploy, and operate AI solutions efficiently, securely, and in alignment with organizational standards. You will act as a technical enabler, helping teams bring AI-driven applications into production while ensuring best practices across architecture, compliance, DevSecOps, FinOps, and AI governance. The role also includes direct contributions to the platform itself.
Your Impact
Enhance DevOps platform capabilities to support AI-based tools and workloads.
Work closely with development teams to enable and support AI application delivery end-to-end.
Assist in designing architecture and production-grade implementation of AI systems.
Lead and enforce DevSecOps practices, compliance requirements, and governance standards for AI solutions.
Develop platform components and internal services as part of the AI infrastructure layer.
Support production readiness, monitoring, performance, reliability, and cost optimization (FinOps).
Serve as a technical interface between multiple engineering teams.
Participate in future on-call rotations.

We are seeking an experienced and talented backend principal software engineer to work with Java in a Spring Boot framework and a microservices architecture. You will face challenges in algorithmics, architecture, and scalability, requiring you to master new technologies and become productive in a short time. You will work with cutting-edge technologies bound to become the next standards in the security industry.
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Your Impact
Take part in the development of a large and complex cloud security solution for large organizations.
Master cloud security to develop the most advanced cloud security solution in the market.
Write clean, testable, readable, scalable and maintainable Java code that scales and performs well for thousands of customers.
Develop using the most advanced Java technologies to date.
Design your features in an advanced architecture model built to meet the scalability requirements by our large customers.

Palo Alto Networks is 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.

Palo Alto Networks is 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.

Your Career:
Own and continuously improve AWS production infrastructure for scalability, reliability, security, performance, and cost.
Run and evolve Kubernetes environments that support fast, safe product delivery.
Drive developer velocity and production safety through better CI/CD pipelines, release workflows, deployment visibility, and GitOps practices.
Improve observability and incident response - reduce alert noise and raise signal quality.
Design and ship AI-assisted operational agents that change how engineers work - triaging monitoring alerts, summarizing incidents, proposing fixes, onboarding new services, answering questions and requests. This is a core part of the role, not a side project.
Build automation and self-service tooling that removes manual work from provisioning, monitoring, incident response, and developer workflows.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, inefficiencies, and automation opportunities.
Partner with engineering, security, product, and leadership to remove bottlenecks and support safe production growth.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.

Required Sr. Technical Product Engineer (Cortex Agentic Endpoint Security)
Job Summary
As a Senior Technical Product Engineer, you will be a key bridge between the product and the field, ensuring our product meets customer needs and that customers maximize its value. You will act as the product expert for customers and field agents, managing technical engagements from pre-sales to post-sales. Your role involves designing integrations and translating customer requirements into scalable product capabilities, ultimately shaping the future of our offerings.
Key Responsibilities:
Collaborate with Sales, Product Management, partners, and customers to drive innovation and ensure secure, scalable adoption of AES solution.
Lead complex, cross-functional projects that shape the product roadmap and align with field-driven priorities.
Design and oversee customer POVs, deployments and integrations (APIs, workflows, security controls) and identify new integration opportunities.
Provide actionable feedback to Product Managers to influence development in areas such as cloud posture, workload protection, and identity management.
Design and deliver automation content, playbooks, and lead enablement initiatives across partners, sellers, and customer facustomer-facingcing roles.
Advocate for best practices in securing modern application architectures using automation, contextual risk insights, and risk driven policies.

We are looking for a highly motivated AI Research Student for our Robotics & Simulation AI team. You will be passionate about data science, AI quality measurement, and the intersection of AI with high-accuracy industrial domains. This role is ideal for someone who grows with challenging existing assumptions, defining rigorous evaluation methodologies, and pushing AI systems toward measurable reliability. You will combine strong data science and research skills with hands-on experimentation in a production AI product that controls robotic manufacturing simulations.

Key Responsibilities

AI Quality & Stability Research

Define and implement metrics to measure the stability, accuracy, and reliability of our production AI Copilot (PSCoPilot)
Design evaluation frameworks for AI agents operating in safety-critical robotics and simulation environments
Build observability and tracing pipelines using platforms like Langfuse to monitor Copilot performance, token usage, latency, and tool-calling success rates
Analyze failure modes, hallucination patterns, and tool-calling accuracy across 48+ MCP-exposed robotic operations
Develop automated regression and benchmark pipelines to track Copilot quality over time

Data Science & Experimentation

Conduct statistical analysis on Copilot interactions (tool selection accuracy, collision detection correctness, path planning success rates)
Research and apply techniques from AI evaluation literature (LLM-as-judge, human-in-the-loop validation, domain-specific benchmarks)
Leverage LangChain and similar orchestration frameworks to prototype evaluation chains, structured agent workflows, and comparison experiments
Explore how multi-layer agent architectures (fast triage + deep execution) affect accuracy and cost trade-offs
Challenge the team with data-driven insights on where the Copilot underperforms and why

Domain AI Research

Investigate how to improve AI reasoning for robotics tasks requiring high precision (welding, clearance checking, reachability analysis)
Research grounding techniques that reduce errors in domains with zero tolerance for incorrect outputs
Explore and apply new AI technologies (GenAI tools, AI coding assistants, agents, MCP-based solutions) to enhance Copilot capabilities
Validate technical feasibility through hands-on experimentation with our production MCP bridge and two-layer streaming agent engine

Communication & Documentation

Document findings, benchmarks, and technical recommendations
Present results to technical and business partners
Collaborate with the team to translate research insights into production improvements

In this role you will be responsible for designing, developing, implementing and supporting our PLM Product, Teamcenter. You will have the opportunity to work on some of the largest PLM projects in the region, often within regulated environments. We are happy to train you up in our market-leading PLM product.


This role can be based Airport City, Israel. Hybrid working is available, but you must be willing to travel to our customer sites.

A security classification is required for this position. Candidates with a valid, existing security classification are preferred.



How will you shape the world of tomorrow? Digitally and with a future-oriented mindset!

Participate in large Teamcenter implementation projects for the Israeli customers
Understand the goals of the project workstream to which you are assigned, the breakdown of project tasks, and be able to explain the workstreams' relationship to the overall solution
Designing, configuring, testing, data migration, production, and postproduction support
Support knowledge transfer (deliver training courses, user guides, coaching of Teamcenter key users)
Provide ongoing support and troubleshooting
Support the documentation and development of standard methodologies and the further development of our knowledge base

In this role you will be responsible for designing, developing, implementing, and supporting our MES Product, Opcenter. You will have the opportunity to work on some of the largest MES projects in the region, often within regulated environments.

We are happy to train you up in our market-leading MES product.

A security classification is required for this position. Candidates with a valid, existing security classification are preferred.

This role can be based Airport City, Israel. Hybrid working is available, but you must be willing to travel to our customer sites.


How will you shape the world of tomorrow? Digitally and with a future-oriented mindset!

Participate in large MES implementation projects for the Israeli customers
Understand the goals of the project workstream to which you are assigned, the breakdown of project tasks, and be able to explain the workstreams' relationship to the overall solution
Configuration and implementation of end-to-end MES solutions
Testing, data migration, production, and postproduction support
Support knowledge transfer (deliver training courses, user guides, coaching of MES key users)
Support the documentation and development of standard methodologies and the further development of our knowledge base
Ensure solution implementation with special consideration of the surrounding MES and ERP landscape as well as production/quality processes
Acting as part of a Consulting Services team, work productively with Consultants, Architects, Project Managers, and other internal & external interfaces to ensure that the customer succeeds in their objectives
Be a technical trusted advisor to a customer and implement customer requirements to introduce or further develop innovative and integrated MES solutions in production, quality, and compliance management

Appdome's mission is to protect every mobile app in the world and the people who use them. We are the leader in AI-native mobile business protection, providing cyber and fraud teams with an agentic platform that builds, monitors, and maintains security defenses in Android and iOS apps — with no SDKs, no coding, and no disruption to engineering cycles.
Our platform delivers over 400 security, anti-fraud, anti-bot, and API protection capabilities, powered by deep learning models trained on a decade of mobile defense data and trillions of live threat events. From build time to runtime, Appdome's AI Agents help mobile brands detect, investigate, and respond to threats faster than ever — recognized as the best AI Platform for Cyber Resilience at RSA Conference 2026 for the second consecutive year. Leading financial, healthcare, m-commerce, and B2B brands rely on Appdome to secure over 50,000 mobile apps and protect more than 1 billion end users globally.
Appdome is an Equal Opportunity Employer. We are committed to diversity, equity, and inclusion in our workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment without regard to any of these characteristics.
About the Role We are looking for a talented Software Engineer to join Appdome's Identity Group. You will take part in building advanced fraud detection capabilities, working closely with security researchers and data teams to develop cutting-edge solutions that protect hundreds of millions of mobile devices.
Responsibilities
* Design and develop core components of fraud detection systems from early prototyping through production-ready releases.
* Build scalable backend services and distributed systems that process data at scale.
* Work with large-scale datasets and collaborate with data teams to create actionable signals and features.
* Write high-performance, production-quality code in C and C++ optimized for reliability and performance.
* Take ideas from rapid proof-of-concept through to production, tackling complex engineering challenges across the full development lifecycle.

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.

This is a hands-on, cross-functional role ideal for engineers who love building full-fledged features-from data pipelines and LLM orchestration to intuitive UI experiences-with a strong product mindset.

Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.