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This is a full-time on-site role located in Haifa for a SecOps professional. The responsibilities include maintaining and optimizing security operations, identifying and mitigating potential vulnerabilities, implementing security monitoring solutions, and responding to security incidents. The role involves working collaboratively with cross-functional teams to ensure the deployment of robust security measures and policies across systems and infrastructures.

We seek a senior staff-level product security engineer to serve as a senior technical authority within the Product Security Incident Response Team (PSIRT). PSIRT is our awareness, response, and investigation capability for post-release vulnerabilities in our-developed products and service offerings.
This role is for a recognised expert who can operate independently and as part of a team on the most significant security issues facing the platform-vulnerabilities that require evaluating intangibles. You will lead deep-dive investigations, coordinate resolution across engineering, product, and release teams, and demonstrate calm, decisive leadership during significant security events.
This is a role for someone who already understands product development cycles and the engineering and product relationships that drive them-and will use that fluency to lead fixes to completion under incident pressure. You will help shape how we respond to product security vulnerabilities at scale and the technical rigour of the entire response capability.
The coverage provided by this role is:
Sunday: 10:00 - 18:00 UTC.
Monday: 08:00 - 16:00 UTC.
Tuesday: 08:00 - 16:00 UTC.
Wednesday: 08:00 - 16:00 UTC.
Thursday: 08:00 - 16:00 UTC.
Due to the nature of incident response and the needs of the business, coverage may change. Additional coverage outside of stated hours may be required in response to significant incidents.
Key Responsibilities:
Lead Through Significant Security Events:
Demonstrate technical and organisational leadership during these events-bringing structure and clear decision-making under pressure.
Partner with incident commanders, business information security leadership, engineering, and customer-facing teams to maintain clear ownership, workstream prioritization, and hand-offs during these events.
Reduce Exposure Window:
Drive coordinated response across affected releases, balancing risk and remediation feasibility.
Leverage an understanding of product development cycles and engineering/product partnerships to move fixes through the release pipeline without stalling on organisational boundaries.
Verify fix completeness and guard against incomplete mitigations before release.
Drive the CVE & Coordinated Disclosure Process:
Collaborate with external security partners, vendors, and researchers on coordinated disclosures, aligning timelines and messaging across parties.
Conduct technical accuracy reviews of external advisories, researcher write-ups, and joint disclosure content to ensure correctness before publication.
Represent PSIRT's technical position in multi-party coordinated disclosures and researcher engagements.

We are looking for a Senior Linux Security Developer to design and develop security capabilities deep inside the Linux OS - kernel internals, eBPF, OS telemetry, enforcement mechanisms, and security agents. You will own architecture decisions, investigate new attack
surfaces, prototype novel approaches, and turn successful concepts into production technologies.
What You'll Do:
Design and implement high-performance Linux security components in kernel and user space (kernel modules, eBPF, system services, security agents), including tamper-resistant mechanisms for adversarial environments.
Build scalable Linux endpoint capabilities for telemetry, detection, prevention, and policy enforcement.
Investigate Linux kernel subsystems to find opportunities for new detection and prevention capabilities, including protection of AI-agent workloads (autonomous processes, tool execution, privilege usage, filesystem/network activity).
Translate research ideas into efficient, production-grade implementations (performance, concurrency, reliability, security), and mentor engineers in systems programming and Linux security.

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